Parallel Domain’s mission is to enable our partners to bring autonomy and physical AI to the world faster, safer and with higher quality.
\nWe build sensor simulation and reconstruction software that helps teams developing autonomous vehicles, robotics, drones, eVTOL systems and other physical AI applications test and validate their technology at scale.
\nOur platform turns real-world customer capture data into high-fidelity, physically valid simulation environments, then enables deterministic camera, lidar and radar simulation across the scenarios customers need to evaluate. In autonomy and physical AI, there is no margin for error.
\nParallel Domain is hiring a Director of Sales Engineering to lead the technical side of our enterprise sales process.
\nThis is a hands-on, individual-contributor leadership role for someone who can earn credibility with highly technical buyers, uncover how customers develop and validate autonomous systems, and design evaluations that demonstrate measurable product value.
\nYou will partner closely with our OEM Enterprise Sales Director and Enterprise Sales Director across the full customer journey, from initial technical discovery and architecture review through demonstration, proof of concept, production deployment and expansion.
\nYou will work directly with perception engineers, ML engineers, simulation teams, data leaders, autonomy executives and other technical stakeholders. You will be expected to understand their workflows, identify where Parallel Domain fits within their development and validation infrastructure, and translate technical requirements into a clear path forward.
\nAs an early leader in the commercial organization, you will also build the sales engineering foundation Parallel Domain needs to scale. This includes discovery standards, demonstration environments, evaluation frameworks, reusable technical content, competitive positioning and the operating model between Sales, Product and Engineering.
\n● Own the technical sales cycle for strategic enterprise and automotive OEM opportunities.
\n● Partner with Enterprise Sales Directors to qualify opportunities, shape account strategies and
\nadvance complex deals.
\n● Lead technical discovery with customer teams across perception, machine learning, simulation,
\nautonomy, data infrastructure, validation and engineering.
\n● Understand how customers collect and manage sensor data, train and evaluate models, reconstruct
\nenvironments, run simulation and validate autonomous-system performance.
\n● Translate customer workflows, technical requirements and business objectives into a clear
\nParallel Domain solution.
\n● Deliver technically credible product demonstrations tailored to specific customer use cases and
\narchitectures.
\n● Design and lead proof-of-concept and evaluation engagements with defined use cases, success
\ncriteria, stakeholders, timelines and paths to production.
\n● Ensure technical evaluations remain connected to commercial outcomes and expansion
\nopportunities.
\n● Support customers in understanding how Parallel Domain integrates with existing autonomy
\nstacks, APIs, development environments, data pipelines and CI/CD workflows.
\n● Navigate technical objections, architecture concerns, security questions, integration requirements
\nand competitive alternatives.
\n● Partner with Product and Engineering to scope customer requirements without overcommitting or
\ncreating unsustainable one-off solutions.
\n● Represent the voice of the customer internally by providing structured feedback on product gaps,
\nrecurring use cases, market needs and competitive dynamics.
\n● Build repeatable sales engineering processes, including discovery frameworks, demo assets,
\ntechnical qualification standards, POC templates and evaluation scorecards.
\n● Develop technical materials that support the sales process, including solution briefs, architecture
\ndiagrams, technical proposals, evaluation plans and responses to customer requirements.
\n● Support the transition from technical validation into onboarding, deployment and expansion.
\n● Represent Parallel Domain at customer meetings, automotive and autonomy conferences,
\ntechnical events and industry forums.
\n● Help define the future structure, hiring profile and operating model for the Sales Engineering
\nfunction as the company grows.
\n● 8+ years of professional experience in technical software, infrastructure, machine learning, simulation, autonomy, robotics, developer tools or a related field.
\n● 5+ years of experience in sales engineering, solutions architecture, customer engineering, technical consulting or another customer-facing technical role.
\n● Experience supporting complex enterprise sales cycles involving technical evaluations, proofs of concept, architecture reviews and multiple customer stakeholders.
\n● Demonstrated ability to work directly with engineering-oriented buyers and earn credibility through strong technical discovery and communication.
\n● Experience with one or more of the following: autonomous systems, AV or ADAS development, robotics, simulation, synthetic data, computer vision, machine learning infrastructure, sensor data, developer platforms or data infrastructure.
\n● Working knowledge of machine learning development and validation workflows.
\n● Ability to understand and discuss APIs, cloud infrastructure, data pipelines, model evaluation and
\nsoftware integration patterns.
\n● Strong ability to translate technical capabilities into customer value and measurable business
\noutcomes.
\n● Experience defining evaluation success criteria and moving customers from proof of concept to
\nproduction adoption.
\n● Excellent written and verbal communication skills across engineering, product, executive and
\ncommercial audiences.
\n● Strong judgment around when to configure, integrate, escalate, push back or involve Product and
\nEngineering.
\n● Comfort operating in an early-stage environment with ambiguity, limited process and high
\nownership.
\n● Ability to build repeatable systems while remaining deeply involved in customer execution.
\n● Willingness to travel regularly within the United States.
\n\n
● Prior experience as a software engineer, ML engineer, simulation engineer, solutions architect or technical product leader.
\n● Experience selling into automotive OEMs, Tier 1 suppliers, autonomy companies, robotics businesses, drone companies or other physical AI organizations.
\n● Familiarity with camera, lidar, radar or other sensor modalities.
\n● Understanding of perception development, model evaluation, scenario generation, closed-loop
\ntesting or software-in-the-loop simulation.
\n● Experience with Python, APIs, notebooks, cloud environments or technical prototyping.
\n● Experience with production deployments of developer-facing, infrastructure or data products.
\n● A record of helping close and expand six- or seven-figure enterprise contracts.
\n● Experience building an early sales engineering, solutions or customer engineering function.
\nWithin the first six months, you will:
\n● Establish a consistent technical discovery and qualification process.
\n● Build a repeatable evaluation and POC framework.
\n● Become a trusted technical partner to Parallel Domain’s enterprise sales team.
\n● Independently lead customer demonstrations, architecture discussions and evaluations.
\n● Reduce dependency on Product and Engineering during routine technical sales activity.
\n● Improve the quality, speed and commercial conversion of customer evaluations.
\nOver time, you will help Parallel Domain create a scalable technical GTM function capable of supporting growth across automotive, robotics, drones, trucking, agriculture, defense and other physical AI markets.
\nParallel Domain’s mission is to enable our partners to bring autonomy and physical AI to the world faster, safer and with higher quality.
\nWe build sensor simulation and reconstruction software that helps teams developing autonomous vehicles, robotics, drones, eVTOL systems and other physical AI applications test and validate their technology at scale.
\nOur platform turns real-world customer capture data into high-fidelity, physically valid simulation environments, then enables deterministic camera, lidar and radar simulation across the scenarios customers need to evaluate. In autonomy and physical AI, there is no margin for error.
\nCompensation
\nBase: $170,000–$200,000
\nCompetitive variable (OTE structure)
\nEquity
\nFull benefits
\nWe're looking for an Enterprise Sales Director to own new business across our direct enterprise segment — technical SaaS companies, AV startups, robotics firms, and ML-native organizations. This is a quota-carrying individual contributor role for someone who loves selling to technical buyers: ML engineers, heads of perception, and data operations leaders who care deeply about whether your product actually works.
\nYou know how to earn credibility with smart, skeptical engineering-oriented buyers. You're not expected to out-engineer them — our Technical Engagement Managers are there for that — but you can hold a substantive product conversation and translate technical value into business impact.
\nOwn the full sales cycle for direct enterprise accounts — from prospecting through POC, close, and expansion
\nBuild pipeline and execute deals across AV, robotics, drone, and ML-native companies
\nRun POC engagements as the entry point, with a clear path to standard deals and production-scale expansions
\nPartner with Technical Engagement Managers on product-depth discussions and customer technical evaluations
\nDevelop and maintain accurate pipeline forecasts and account plans
\nRepresent Parallel Domain at industry events, including CVPR, NeurIPS, and robotics/AV conferences
\n6+ years of enterprise sales experience, with a track record selling technical software products to engineering or ML-oriented buyers
\nExperience in one or more of: synthetic data, MLOps, AV/ADAS tooling, robotics software, simulation, or developer infrastructure
\nDemonstrated ability to land and expand 6–7 figure contracts in a startup or high-growth environment
\nComfortable selling to technical champions — you understand the product well enough to earn their respect and move the deal forward
\nEntrepreneurial and self-directed; you can build pipeline from scratch and don't need a large SDR motion to be productive
\nFully remote; travel to customer sites, San Francisco, and industry conferences expected
\nCompensation
\nBase: $170,000–$200,000
\nCompetitive variable (OTE structure)
\nEquity
\nFull benefits
\nWe're looking for an OEM Enterprise Sales Director to own and grow relationships with major automotive OEMs — Ford, GM, Stellantis, and others. This is a quota-carrying individual contributor role for someone who knows how to navigate the complexity of large automotive organizations: how decisions get made, who the real stakeholders are, and how to move from a proof of concept to a multi-million dollar production contract.
\nYou don't need to be an engineer. You need to understand the problem we solve well enough to open the right doors and earn the right conversations — our Technical Engagement Managers handle the deep technical discussions.
\nOwn the full sales cycle for OEM accounts — from initial outreach through POC, expansion, and multi-year contracts
\nNavigate large, complex automotive organizations to identify champions, economic buyers, and decision-making processes
\nRun POC engagements as the entry point with a clear line of sight to standard deals and million-dollar production expansions
\nPartner closely with our Technical Engagement Managers who support you on product-depth conversations
\nBuild and maintain a healthy pipeline and accurately forecast to leadership
\nRepresent Parallel Domain at industry events (CES, CVPR, automotive industry conferences)
\n7+ years of enterprise sales experience, with meaningful time selling into OEM automotive accounts (Tier 1 suppliers, OEM internal technology groups, or similar)
\nDeep understanding of how OEMs make purchasing decisions — org structure, procurement processes, and stakeholder mapping
\nTrack record of landing and expanding 6–7 figure contracts in complex enterprise environments
\nExperience selling technical software or data products; simulation, ADAS tooling, or ML infrastructure a strong plus
\nComfortable holding a product-level conversation without engineering support — you know when to bring in the experts
\nFully remote; travel to Detroit, customer sites, and San Francisco for key meetings and events expected
\nBefore an autonomous vehicle navigates a busy intersection, before a robot learns to pick and place in a warehouse, before any Physical AI system is trusted in the real world, it has to prove itself in ours. Parallel Domain builds the platform that validates the next generation of autonomous systems in high-fidelity virtual environments.
\nOur content and rendering pipeline is how that platform earns its credibility with customers. The virtual environments we build have to hold up under physical, geometric, and sensor-level scrutiny—they are the testbeds against which our customers' autonomous systems are validated. Building environments at that level of fidelity and scale demands techniques that go beyond a typical AAA game pipeline. Gaussian splat scene reconstruction, neural rendering, AI-assisted content workflows, and modern procedural systems are reshaping what a tech artist's day looks like.
\nWe're hiring a Principal Technical Artist to bring the next generation of these workflows into production at Parallel Domain. This is a senior individual contributor role: you'll work alongside our rendering, simulation, and content engineers on open-ended content and pipeline problems. You'll move fluently between Unreal Engine, Houdini, Python, shader code, and modern AI tooling, and your judgment will shape how our team builds the environments that train and validate autonomous systems.
\nOwn the technical content stack. End to end: asset pipelines, procedural tooling, material systems, performance budgets, and content validation that turn an artist's intent into a production-ready scene.
\nBuild and ship tools. Deliver tooling in Unreal Engine and Houdini that makes the content team measurably faster. We care less about the elegance of the tool and more about whether artists are using it next quarter to ship work they couldn't ship before.
\nDrive AI-augmented workflows. Bring modern techniques into content creation: gaussian splat scene reconstruction, neural texture synthesis, ML-assisted asset generation, and the next wave of techniques as they emerge. Hold an opinionated view on where these tools belong in a production pipeline and where they don't.
\nOptimize real-time performance. Profile and optimize across GPU and CPU in Unreal Engine, supporting both interactive use and large-scale batch simulation. Identify bottlenecks, codify the fixes as patterns, and make sure the team isn't relearning the same lessons every six months.
\nWork across disciplines. Operate as connective tissue across content, rendering, simulation, ML, and product. Translate between disciplines, broker tradeoffs between content fidelity and runtime performance, and make sure the systems we build hang together.
\nSet the craft bar. We're not asking you to manage people, but we expect you to lead by example on the craft side. Your work should make the people around you better at theirs.
\nMove quickly. Ship into production early and often. Many of the problems you'll work on don't have a known answer—your job is to scope the unknown, prototype something that works, and harden it from there.
\nExperience. 8+ years as a technical artist or in a closely adjacent role, with at least one shipped product on a real-time, physically based rendering pipeline.
\nUnreal Engine 5 expertise. Expert-level proficiency including materials, Blueprints, performance profiling, the asset pipeline, and the engine's deeper rendering features. You can debug a frame budget, fix a broken shader, and ship a Blueprint utility in the same afternoon.
\nProgramming fluency. Productive across some combination of Python, C++, HLSL, VEX, and shell. You reach for code rather than manual process whenever possible.
\nProduction speed. Demonstrated ability to take open-ended content or workflow problems, scope them yourself, and ship working systems the team adopts—without extensive hand-holding.
\nAI workflow fluency. Working command of LLM-based coding tools, generative content tooling (e.g., diffusion models, ComfyUI), and the broader category of AI tools reshaping technical art. You stay on top of where these tools are heading and bring that thinking into the team's practice.
\nCommunication. Equally comfortable talking shaders with rendering engineers, performance with simulation engineers, and tradeoffs with non-technical product partners.
\nNeural scene reconstruction. Hands-on experience with gaussian splatting, NeRFs, or similar techniques in a production or near-production setting.
\nProcedural content generation. Experience in Houdini or equivalent (Maya, Blender, 3DS Max, Unreal PCG), including authoring HDAs and integrating them into a real-time pipeline.
\nSensor simulation. Familiarity with RGB cameras, LiDAR, radar, and the visual artifacts that matter to autonomous-system perception models.
\nDistributed/cloud pipelines. Experience with distributed rendering or cloud-based content pipelines.
\nIn your first six months, you'll have:
\n\nIntegrated into the production pipeline and shipped meaningful content using our in-house tools.
\nDelivered tooling in Houdini or Unreal Engine that improves content team velocity.
\nBuilt strong working relationships with engineering, simulation, rendering, and DevOps stakeholders.
\nInfluenced the technical roadmap with at least one concrete bet that ships customer value.
\nBefore an autonomous vehicle navigates a busy intersection, before a robot learns to pick and place in a warehouse, before any Physical AI system is trusted in the real world, it has to prove itself in ours. Parallel Domain builds the platform that validates the next generation of autonomous systems in high-fidelity virtual environments.
\nOur content and rendering pipeline is how that platform earns its credibility with customers. The virtual environments we build have to hold up under physical, geometric, and sensor-level scrutiny—they are the testbeds against which our customers' autonomous systems are validated. Building environments at that level of fidelity and scale demands techniques that go beyond a typical AAA game pipeline. Gaussian splat scene reconstruction, neural rendering, AI-assisted content workflows, and modern procedural systems are reshaping what a tech artist's day looks like.
\nWe're hiring a Principal Technical Artist to bring the next generation of these workflows into production at Parallel Domain. This is a senior individual contributor role: you'll work alongside our rendering, simulation, and content engineers on open-ended content and pipeline problems. You'll move fluently between Unreal Engine, Houdini, Python, shader code, and modern AI tooling, and your judgment will shape how our team builds the environments that train and validate autonomous systems.
\nCompany Overview
\nParallel Domain is the trusted sensor simulation and reconstruction software for physical AI. We turn customer capture data into real-fidelity replicas with deterministic multi-sensor simulation running on top. The largest autonomy programs in the world use our products to validate perception at the scale that safety demands.
\nThey are a Series B company backed by March Capital, Foundry Group, Costanoa Ventures, Toyota Ventures, and others. Their team includes engineers from Waymo, Cruise, Apple, NVIDIA, and Google. They are fully remote and growing fast.
\nHow long has the company been operating? 2017
\nTotal company headcount: 50+
\nOur mission is to enable our customers to bring autonomy and physical AI to the world faster and safer. We believe physical AI and autonomy have the power to create a safer and more productive world, and we are building the simulation infrastructure to make that future real. Our high-fidelity, fully controllable, software-in-the-loop sensor simulation products give the leaders in autonomous driving, drone delivery, eVTOL, robotics, and beyond the realism, accuracy, and confidence they need to test and validate their systems at scale. In autonomy and physical AI, there is no margin for error.
\nWe are hiring a Product Manager to work directly with our Chief Product Officer in managing our suite of simulation and neural reconstruction products. This role will be an exciting blend of hands-on product work, customer interactions, and strategic product roadmapping.
\nThis is a highly technical role. Our users are AI developers and our product heavily leverages cutting edge simulation technologies. This role requires expertise in AI development, simulation technologies, product management, and programming. By spending significant time with our customers, including automotive, drone, and robotics companies, you will become an expert in how our customers need to use simulation to accelerate their development of autonomous systems and then put this expertise at work to help Parallel Domain build winning products.
\nThis role is ideal for someone who thrives in ambiguous environments, enjoys solving complex technical challenges, and can translate customer needs into scalable product capabilities.
\nCompany Overview
\nParallel Domain is the trusted sensor simulation and reconstruction software for physical AI. We turn customer capture data into real-fidelity replicas with deterministic multi-sensor simulation running on top. The largest autonomy programs in the world use our products to validate perception at the scale that safety demands.
\nThey are a Series B company backed by March Capital, Foundry Group, Costanoa Ventures, Toyota Ventures, and others. Their team includes engineers from Waymo, Cruise, Apple, NVIDIA, and Google. They are fully remote and growing fast.
\nHow long has the company been operating? 2017
\nTotal company headcount: 50+
\nParallel Domain celebrates diversity and is committed to creating a safe and inclusive environment for all our people. We are committed to providing employees with an environment free of discrimination, bullying and harassment. All employment decisions at Parallel Domain are based on business needs, job requirements and individual qualifications. We will maintain our commitment to and support of equal employment opportunity for all individuals without regard to race, national/ethnic origin, colour, religion, age, sex (including pregnancy), sexual orientation, gender identity/expression, marital status, family status, genetic characteristics or physical/mental disability. Our commitment extends to any other protected classes which may exist under applicable law.
\nBefore an autonomous vehicle navigates a busy intersection, before any Physical AI system is trusted in the real world, it has to prove itself in ours. Parallel Domain builds the platform that validates the next generation of autonomous systems in high-fidelity virtual environments.
\nOur sensor models are how that platform earns its credibility with customers. A simulated camera, lidar return, or radar detection is only useful if it behaves the way the real device behaves — including in the conditions where the real device struggles: heavy rain, snow, low reflectivity, multipath, clutter. Customers train and validate perception stacks against our output, so the physics has to hold up under scrutiny, and we have to be able to demonstrate that against measured data rather than assert it. That bar is rising as the modalities we simulate expand and the questions customers ask get sharper.
\nWe're hiring a Senior Sensor Simulation Engineer to lead that work. This is a senior individual contributor and technical lead role: you'll own the technical direction for our sensor simulation portfolio — radar as the primary focus, extending across lidar, thermal/LWIR, and the broader multi-modal suite — and you'll be the person who decides where the physics goes next. You'll work hands-on building and validating models in modern C++, and partner with product and engineering leadership on where we invest. You'll be joining a small, deep team where your technical judgment carries real weight from day one.
\nSet sensor simulation direction. Own the multi-quarter technical roadmap for radar, lidar, and thermal modeling — which fidelity gaps matter, which modalities we add, and how the work sequences. You'll be the company's authority here, and product strategy in this area will follow your read of where the industry is heading.
\nBuild physically accurate sensor models. Radar as the primary focus — RF propagation, RCS, Doppler, multipath, antenna patterns, and raw pre-detection output — extending across lidar and thermal/LWIR. Real implementation work in modern C++ against a real-time rendering pipeline, deterministic and reproducible frame to frame.
\nValidate against real sensor data. Define the metrics and methodology that quantify how close our output is to measured reality, and drive model improvements from what that analysis tells you. We want to move from \"this looks right\" to \"here is the correlation, here is the error distribution, here is what we fixed.\"
\nModel the hard conditions. Weather and environmental effects — rain, wetness, snow accumulation, low visibility — are where sensor fidelity gets interesting. Expect heuristics as well as first-principles physics, and the judgment to know which the problem calls for.
\nSet the standard for scientific rigor. Extend the validation discipline you bring on radar and lidar across the rest of the sensor suite, camera included. If we're going to call ourselves a sensor simulation company, the testing has to back it up.
\nPartner with perception and ML teams. Translate real-world perception failure modes into concrete, prioritized fidelity requirements — both internally and in technical conversations with customers evaluating our output.
\nGrow the team's depth. Provide technical direction to the engineers working in this area, and raise the bar on how the broader team reasons about sensor physics.
\nUse AI tooling actively. LLM-assisted coding and literature review meaningfully accelerate this kind of work. We expect fluency here — the bottleneck in this role is physical insight, not typing speed, and we want you spending your time on the former.
\nExperience. A track record of building simulation, sensor-modeling, or computational-physics software that was actually deployed and relied upon. We weight demonstrated physical insight above years served — a recent PhD with the right depth and a fifteen-year radar veteran are both credible here.
\nPhysics-first foundation. Strong grounding in physics, applied physics, or electrical engineering — frequently an MSc or PhD, though we care about the depth of understanding rather than the credential. You can read a paper, work through the math, and turn it into working code.
\nRadar and RF depth. Radar signal processing, automotive or industrial radar domain experience, or a closely adjacent RF/electromagnetics background you're ready to apply to simulation. Candidates currently in radar algorithm roles who want to move into simulation are very much in scope.
\nSensor physics breadth. Deep grounding in the physics of one or more sensing modalities — radar/RF, lidar, thermal/infrared, or electro-optical — and the underlying math: EM propagation, signal processing, radiometry, linear algebra.
\nValidation rigor. Demonstrated experience validating models against real measured sensor data and reasoning carefully about accuracy, error, and what a discrepancy is actually telling you.
\nProductive in C++. Our engineering team works primarily in modern C++. You don't need to be a language expert, but you must be genuinely effective at writing, debugging, and extending performance-sensitive code in a large multi-library codebase with a real build system and CI.
\nTechnical leadership. Ability to set direction, not just execute it — to look at a domain, form a view on where it's going, argue for it, and then deliver against it.
\nCommunication. Comfortable moving between a physics discussion with a researcher, an implementation discussion with a graphics engineer, and a roadmap discussion with product and executive stakeholders.
\nRaw radar simulation. Experience modeling pre-detection radar output — ADC-level, range-Doppler, or point-cloud-before-clustering — rather than object-level detections.
\nThermal and LWIR. Thermal imaging or radiometric modeling background, including material emissivity and thermal scene modeling.
\nCommercial sensor simulation. Time spent building or working on commercial sensor simulation software, or inside a Tier-1 or OEM sensor team.
\nReal-time engines. Experience with Unreal Engine or a comparable real-time engine, or with bridging physics-heavy C++ against a rendering pipeline.
\nGPU and ray tracing. Physics engines, ray tracing, or GPU compute for large-scale sensor simulation.
\nDomain context. Autonomous vehicles, robotics, ADAS, or aerospace sensing.
\nIn your first six months, you'll have:
\n\nShipped meaningful improvements to our radar model that measurably close the gap against real sensor data, with the validation results to prove it.
\nPublished a sensor simulation technical roadmap that engineering, product, and leadership align around.
\nEstablished a validation methodology and metric set that the team uses as the standard for judging fidelity.
\nBecome a credible technical voice with customers evaluating our sensor output.
\nBase salary range of $155,000 to $175,000, commensurate with skills, qualifications, and experience.
\nThis role is fully remote within North America. Our company operates on PST working hours.
\nWe are assembling a team of creative, talented visionaries seeking to build a new technology that will change the world. You will be able to learn, build, and scale our team and technology in a collaborative, creative culture that values every team member.
\nTo attract and inspire the right talent, we offer:
\n\nEquity
\nEmployer-paid supplemental medical, mental health, dental, and vision benefits
\nFlexible paid vacation, sick time, winter shutdown, and 11+ holidays per year
\nPaid parental leave
\nEquipment budget to optimize your setup
\nAnnual learning and development stipend
\n\n
Before an autonomous vehicle navigates a busy intersection, before any Physical AI system is trusted in the real world, it has to prove itself in ours. Parallel Domain builds the platform that validates the next generation of autonomous systems in high-fidelity virtual environments.
\nOur sensor models are how that platform earns its credibility with customers. A simulated camera, lidar return, or radar detection is only useful if it behaves the way the real device behaves — including in the conditions where the real device struggles: heavy rain, snow, low reflectivity, multipath, clutter. Customers train and validate perception stacks against our output, so the physics has to hold up under scrutiny, and we have to be able to demonstrate that against measured data rather than assert it. That bar is rising as the modalities we simulate expand and the questions customers ask get sharper.
\nWe're hiring a Senior Sensor Simulation Engineer to lead that work. This is a senior individual contributor and technical lead role: you'll own the technical direction for our sensor simulation portfolio — radar as the primary focus, extending across lidar, thermal/LWIR, and the broader multi-modal suite — and you'll be the person who decides where the physics goes next. You'll work hands-on building and validating models in modern C++, and partner with product and engineering leadership on where we invest. You'll be joining a small, deep team where your technical judgment carries real weight from day one.
\nParallel Domain builds synthetic data and simulation platforms for autonomous vehicle and robotics teams. The Product Engineering team owns the customer-facing product and service layer: the self-serve platform for productizing ML reconstruction pipelines, our high-fidelity simulation-as-a-service product, the web applications and dashboards customers interact with directly, and the centralized backend services and APIs that connect them.
\nWe're hiring a Senior Software Engineer to own delivery across this stack. You'll design and build features and services end to end - from API design through to production - and take real ownership of the reliability and quality of what you ship. Our stack spans Python backend services, RESTful and gRPC APIs, relational databases, React frontends, and data pipelines. Engineers who thrive here are comfortable across multiple layers of the stack, move well from a requirement to a design, and take operational ownership of what they build.
\nExpand and maintain customer-facing services and APIs. You'll build and improve the services customers interact with directly: interactive services and async processing pipelines, web app integrations, and APIs that connect them.
\nDesign and implement APIs and data models. You'll architect and implement RESTful API endpoints that cleanly separate data from business logic, are well-documented, and are built to the standards customers and field engineers depend on.
\nCollaborate across product, SRE, and field engineering. You collaborate with product managers and technical stakeholders to understand requirements and clarify interface design. You partner with SRE on deployment and operational concerns.
\nOwn features end to end. You'll design, implement and ship solutions, and keep them running. You're not done when the PR merges.
\nDebug production issues and improve service reliability. You'll contribute to observability, alerting, and the ongoing health of the services your team operates. You participate in incident response and drive root-cause improvements.
\nUphold and contribute to engineering standards. You follow and help shape team standards around testing, code quality, API documentation, dependency management, and service structure. You leave the codebase better than you found it.
\nTrack record of delivering complex backend features. You've owned non-trivial backend projects end to end - from design through to production - across APIs, databases, and service integrations.
\nAPI design experience. You're comfortable designing RESTful APIs: resource modeling, separation of data and business logic, authentication, versioning, and documentation. You understand what makes an external-facing API maintainable.
\nPython web frameworks and relational databases. Hands-on experience with Flask, FastAPI, or equivalent frameworks; PostgreSQL or similar; ORM patterns; and writing production-grade backend code.
\nContainerized deployment. Experience deploying, operating, and debugging services on Linux using Docker and Kubernetes.
\nProduction service ownership. You've owned services in production: monitoring, alerting, on-call response, and the follow-through after an incident.
\nRequirement gathering and collaboration. You can work with product and customer-facing stakeholders to clarify requirements, surface interface design questions early, and produce concrete designs before implementation starts.
\nLanguages and Frameworks. Python, FastAPI, Flask, PostgreSQL, React, TypeScript
\nSystems & Infrastructure. AWS (S3, RDS, Lambda, EKS), Docker, Kubernetes, GitHub Actions, Jenkins, gRPC, Proto
\nDomain Experience. RESTful API design and documentation. Production service ownership. Data pipeline operation. Observability tooling (Prometheus, Grafana). Experience in simulation, ML pipelines, or autonomous systems is an advantage.
\nExperience with event-driven systems and message brokers (e.g., Redis, SQS, RabbitMQ)
\nExperience with workflow orchestration tools (e.g., Apache Airflow)
\nFamiliarity with load balancers, HTTP proxies, or service mesh patterns
\nExperience with ORMs such as SQLAlchemy
\nBackground supporting production monitoring databases and alerting infrastructure
\nPrimary ownership of a production React web application, including architecture, state management, and deployment
\nExperience with frontend testing, build tooling, or performance optimization
\nParallel Domain builds synthetic data and simulation platforms for autonomous vehicle and robotics teams. The Product Engineering team owns the customer-facing product and service layer: the self-serve platform for productizing ML reconstruction pipelines, our high-fidelity simulation-as-a-service product, the web applications and dashboards customers interact with directly, and the centralized backend services and APIs that connect them.
\nWe're hiring a Senior Software Engineer to own delivery across this stack. You'll design and build features and services end to end - from API design through to production - and take real ownership of the reliability and quality of what you ship. Our stack spans Python backend services, RESTful and gRPC APIs, relational databases, React frontends, and data pipelines. Engineers who thrive here are comfortable across multiple layers of the stack, move well from a requirement to a design, and take operational ownership of what they build.
\nParallel Domain is the trusted sensor simulation and reconstruction software for physical AI. We turn customer capture data into real-fidelity replicas with deterministic multi-sensor simulation running on top. The largest autonomy programs in the world use our products to validate perception at the scale safety demands.
\nWe are a Series B company backed by Foundry Group, Costanoa Ventures, Toyota Ventures, and others. Our team includes engineers from Waymo, Cruise, Apple, NVIDIA, and Google. We are fully remote and growing fast.
\nWe are hiring a Technical Account Director to own highly strategic relationships with OEM customers with multiple entities in their corporate families. These are multi-year enterprise engagements with stakeholders across engineering, perception, planning, and executive leadership in both the US and Japan. The stakes are high and the accounts are growing.
\nYou will be the single point of contact for this account. You own the relationship, the program, and the commercial expansion. You run the cadence, you build the org map, and you drive alignment across every active workstream. Engineers, FDEs, product, and executives all plug into the account through you.
\nThis is a technical role. You will sit in rooms with perception leads, simulation engineers, and ML infrastructure architects and you need to hold your own. You need to understand the sim-to-real gap, how sensor simulation works, what makes a replica production-grade, and where the hard tradeoffs live in customer integration. You do not need to write code. You do need to anticipate where a technical approach might hit a wall and proactively recommend a better path. You also need to know when to pull in our FDEs and engineers for hands-on product depth.
\nOwn the account end to end: relationship, technical guidance, commercial, escalations, expansion, and renewal.
\nBe the single point of contact for every inbound and outbound communication with the customer. Set and hold internal SLAs on response times.
\nGuide the customer's technical approach to integration, simulation usage, and replica adoption. Spot risks early and proactively recommend the path that gets them to production faster.
\nProgram manage 5 to 8 concurrent workstreams across PD and customer teams, driving alignment on status, progress, blockers, and decisions between both sides.
\nBuild and maintain a deep org map across the customer's corporate family: decision makers, champions, blockers, budget holders, and how the entities connect to each other.
\nRun the customer cadence: weekly tactical syncs with the working team, monthly steering with leadership, quarterly executive business reviews with our exec team.
\nDrive multi-year account planning, expansion into new teams and use cases, and pricing conversations.
\nCoordinate internal PD resources (FDEs, engineering, product, finance, legal) so the customer sees one face and gets one answer.
\nPartner with our executive sponsors on the most senior customer relationships.
\nAn engineering background. BS or MS in computer science, electrical engineering, mechanical engineering, robotics, or a related field. You started your career as an engineer and transitioned into customer-facing technical roles.
\n8+ years of experience, with meaningful time owning complex enterprise technical accounts. Experience with global OEM customers is a strong plus.
\nTechnical fluency in simulation, perception, sensor systems, ADAS tooling, ML infrastructure, or autonomous systems. You can discuss sim-to-real gap, lidar modeling, camera ISP pipelines, or HD map ontology without leaning on a teammate for every question.
\nTrack record of managing multi-million dollar enterprise relationships at the depth this role requires. You have owned expansion, pricing, and strategic planning, not renewals alone.
\nDeep understanding of how large, matrixed organizations make decisions: org structure, procurement cycles, stakeholder dynamics, and the difference between a champion and a decision maker.
\nProgram management instinct. You naturally track multiple concurrent workstreams, hold people to deadlines, and surface blockers before they become crises.
\nStrong commercial judgment: you drive contract structure, pricing, and expansion conversations. Relationship management is table stakes, not the ceiling.
\nCalm under pressure. This account has weight, visibility, and urgency. You absorb that and keep the team moving.
\nFully remote. Must be willing to travel internationally, including Japan.
\n3 to 5 years as an IC engineer at an OEM, Tier 1, or AV company before moving into customer-facing roles.
\nExperience as a Technical Program Manager, Technical Account Director, or Customer Engineering Lead at a simulation, developer tools, or autonomous systems company.
\nExperience managing OEM relationships in automotive or trucking, especially with international stakeholders.
\nFamiliarity with closed-loop simulation, scenario-based testing, or sensor-in-the-loop workflows.
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