New offer - be the first one to apply!

June 24, 2026

Senior Embedded Software Engineer

Senior • Hybrid

Pittsburgh, PA

Mission Summary

Motional's onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve the next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for the current and next-generation onboard autonomous driving system. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing

  • Design and develop infrastructure software on various hardware platforms for applications such as vision processing, radar systems, and safety monitoring to be run on self-driving vehicles.
  • Design test harnesses for embedded software components and full systems.
  • Provide technical mentorship to engineers.
  • Proactively work with cross-functional engineering teams to solve complex and interesting problems.

What We're Looking For

  • Experience with creating detailed requirements from use cases.
  • Ability to lead a technical initiative, including breaking down work and guiding other engineers through execution.
  • Experience writing software for embedded platforms in C and C++.
  • Experience with Test-Driven Development (TDD).
  • Experience working on embedded Linux / RTOSs.
  • Experience working with networks (Ethernet, CAN etc.) and the common networking protocols.
  • Experience with debugging on embedded platforms.
  • Experience writing software in Python and experience doing automation with shell scripting.
  • Experience working with ARM Cortex MCUs or Microprocessors.

Bonus Points (not required)

  • Experience working with large data pipelines, and platforms that require deterministic execution.
  • Experience using inter-system communication protocols such as I2C and SPI.
  • Experience deploying Machine Learning models.
  • Experience working with GPUs.
  • Experience working directly with the Linux kernel or Device Drivers.
  • Experience with Simulation and Code Generation, and knowing when their use is appropriate.
  • Experience working with Bazel.
  • Experience integrating various sensors, including Cameras, IMUs, Radars, LIDARs.
  • Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks.

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.

Compensation & Benefits

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity.

Candidates for certain positions are eligible to participate in the benefits program. Benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range:
$149,000—$198,500 USD

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Hybrid

Las Vegas, NV

🏢 Summary: Senior technical leadership role responsible for defining and architecting large-scale machine learning systems that power multimodal data discovery and model improvement for autonomous driving. The position focuses on building scalable ML frameworks, optimizing real-time inference across GPU/CPU clusters, and leading cross-functional initiatives from roadmap to production. You will mentor engineers, set ML engineering standards, and drive department-level technical strategy. 🗂️ Requirements: BS in Computer Science, Machine Learning or related field, 8+ years of hands-on ML engineering experience, Proven ownership of architecture, deployment and optimization of large-scale ML systems, Experience with multimodal foundation models in production, Technical leadership in defining roadmaps and leading multi-person initiatives, Expert proficiency in Python, Strong experience with PyTorch, TensorFlow or JAX, Strong software engineering fundamentals (system design, CI/CD, containerization), Experience deploying ML models in AWS, GCP or Azure, Experience optimizing ML systems for latency, throughput and hardware efficiency 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, LiDAR, Radar 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding rare edge cases, long-tail scenarios, and model errors. Omnitag, our ML-powered multimodal data mining framework, powers this discovery. As a Staff Machine Learning Engineer, you will define the roadmap and architecture for machine learning systems that power data discovery and model improvement lifecycles. You will architect scalable systems spanning multimodal representation learning, active learning loops, and optimized production inference. You will own system-level architecture, lead multi-quarter initiatives, and partner across engineering teams to influence technical strategy and ensure ML platforms serve as a mission-critical engine for the autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: - Develop and execute multi-quarter technical roadmaps for core ML systems - Guide reprioritization to drive team-wide and department-level OKRs and KPIs Architect System-Level Solutions: - Own system-level architecture for complex ML products - Design scalable frameworks for large-scale data mining and real-time inference across GPU/CPU clusters Drive Cross-Functional Execution: - Lead multi-person projects across teams - Influence partner teams' technical roadmaps and build alignment Elevate Engineering Excellence: - Establish standards for ML system design, code quality, testing, and deployment - Deliver processes to proactively address issues and participate in incident response planning Operate as a Generalist Expert: - Apply deep learning, representation learning, active learning, and generative AI to complex problems - Unblock teams facing unprecedented technical challenges Mentor and Lead: - Coach senior and junior engineers - Lead architectural reviews and contribute to engineering culture What We're Looking For (Must-Haves): - BS in Computer Science, Machine Learning, or related field (or equivalent experience) - 8+ years of hands-on ML engineering experience - Proven track record owning architecture, deployment, and optimization of large-scale ML systems - Experience with multimodal foundation models in production systems - Demonstrated technical leadership across multi-quarter initiatives - Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) - Strong software engineering fundamentals (system design, CI/CD, containerization) - Broad ML expertise across model training, deep learning architectures, evaluation, and production deployment - Experience deploying ML models in AWS, GCP, or Azure - Ability to mentor peers and drive consensus across teams Bonus Points: - MS or PhD in Computer Science, Machine Learning, or related field - Background in autonomous driving, robotics, or real-time decision systems - Experience with large-scale ML data mining and active learning loops - Familiarity with multimodal learning and sensor fusion - Experience with model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms - Experience leading incident response planning for mission-critical ML platforms Benefits: - Hybrid or fully remote work options - Base salary range: $205,000—$272,500 USD - Eligibility for bonus or company equity - Medical, dental, vision coverage - 401k with company match - Health savings accounts - Life insurance - Pet insurance

Technology

New offer

Motional

Staff Machine Learning Engineer

Senior

Hybrid

Pittsburgh, PA

🏢 Summary: Senior-level ML engineering role focused on defining architecture and technical strategy for large-scale multimodal machine learning systems powering data discovery and model improvement in autonomous driving. The position leads cross-functional initiatives, builds scalable data mining and real-time inference frameworks, and sets engineering standards across the organization. It combines hands-on system design with technical leadership and mentorship. 🗂️ Requirements: BS in Computer Science, Machine Learning or related field (or equivalent experience), 8+ years of hands-on ML engineering experience, Proven ownership of architecture, deployment and optimization of large-scale ML systems, Experience with multimodal foundation models in production (integration, scaling, fine-tuning, deployment), Demonstrated technical leadership across multi-quarter, multi-person initiatives, Expert-level Python proficiency, Strong experience with PyTorch, TensorFlow or JAX, Strong software engineering fundamentals (system design, CI/CD, containerization), Experience deploying ML models in AWS, GCP or Azure, Experience optimizing ML systems for latency, throughput and hardware efficiency, Ability to mentor engineers and drive cross-team technical alignment 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Docker, Kubernetes, GPU, CPU, DeepLearning, ActiveLearning, GenerativeAI, MLOps, Triton, TorchServe, TFServing 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement lifecycles. Rather than focusing on a single specialized domain, you will leverage your broad ML expertise to architect massive, scalable systems, from multimodal representation learning and active learning loops to hyper-efficient production inference. You will own system-level architecture, lead multi-quarter, multi-person initiatives, and partner across the engineering organization to unblock teams and influence department-wide technical strategy. By establishing robust processes and mentoring others, you will ensure ML platforms act as a reliable, mission-critical engine for the autonomy stack. What You'll Do: Define Technical Strategy & Roadmaps: - Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems - Inform leadership to guide reprioritization aligned with OKRs and KPIs Architect System-Level Solutions: - Own system-level architecture for complex ML products - Design scalable frameworks for massive data mining and optimized real-time inference across GPU/CPU clusters Drive Cross-Functional Execution: - Lead multi-person projects across teams to completion - Influence partner team roadmaps to solve shared problems and build alignment Elevate Engineering Excellence: - Establish standards for ML system design, code quality, testing and deployment - Deliver processes to proactively address issues and participate in incident response planning Operate as a Generalist Expert: - Apply deep learning, representation learning, active learning and generative AI techniques to complex problems - Unblock teams facing unprecedented technical challenges Mentor and Lead: - Coach senior and junior engineers - Lead architectural reviews and contribute to engineering culture through documentation and tech talks What We're Looking For (Must-Haves): - BS in Computer Science, Machine Learning or related field (or equivalent practical experience) - 8+ years of hands-on ML engineering experience with large-scale ML systems - Experience with multimodal foundation models in production systems (camera, LiDAR, radar, text) - Demonstrated technical leadership across multi-quarter initiatives - Expert-level Python and experience with PyTorch, TensorFlow or JAX - Strong software engineering fundamentals including system design, CI/CD and containerization - Experience deploying ML models in AWS, GCP or Azure and optimizing for latency and throughput - Proven ability to mentor peers and drive consensus across teams Bonus Points: - MS or PhD in Computer Science, Machine Learning or related field - Background in autonomous driving, robotics or real-time decision-making systems - Experience with large-scale ML data mining, active learning loops and representation learning - Familiarity with multimodal learning, sensor fusion or large foundation models - Experience with model serving tools such as TF Serving, Triton or TorchServe - Experience leading severity reviews or establishing incident response processes for ML platforms Work Arrangement: Hybrid schedule with in-office time in Boston, Pittsburgh or Las Vegas, or fully remote. Compensation & Benefits: Salary range: $205,000—$272,500 USD (base salary). Additional compensation may include bonus or company equity. Eligible employees may participate in benefits including medical, dental, vision, 401k with company match, health savings accounts, life insurance and pet insurance.

Technology

New offer

Motional

Staff Machine Learning Engineer

Senior

Hybrid

San Francisco, CA

🏢 Summary: Staff Machine Learning Engineer role focused on architecting and leading large-scale ML systems that power multimodal data discovery and model improvement for autonomous driving. The position owns system-level architecture, technical strategy, and cross-functional execution across massive data mining and real-time inference platforms. It combines deep hands-on ML expertise with technical leadership and mentorship at department scale. 🗂️ Requirements: BS in Computer Science, Machine Learning, or related field (or equivalent experience), 8+ years of hands-on ML engineering experience, Proven ownership of architecture, deployment, and optimization of large-scale ML systems, Experience with multimodal foundation models in production (integration, scaling, fine-tuning, deployment), Technical leadership experience defining multi-quarter roadmaps and leading multi-person initiatives, Expert proficiency in Python and at least one major ML framework (PyTorch, TensorFlow, or JAX), Strong software engineering fundamentals (system design, CI/CD, containerization), Broad ML expertise across model training, deep learning, evaluation, and large-scale deployment, Experience deploying ML models in cloud environments (AWS, GCP, or Azure), Ability to mentor engineers and drive cross-team technical alignment 📃 Skills: Python, PyTorch, TensorFlow, JAX, AWS, GCP, Azure, CI/CD, Containerization, DeepLearning, RepresentationLearning, ActiveLearning, GenerativeAI, MultimodalModels, ModelServing, MLOps, GPU, CPU 🏢 Description: Mission Summary: At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, powers this discovery. As a Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for machine learning systems that power data discovery and model improvement lifecycles. You will architect scalable systems spanning multimodal representation learning, active learning loops, and high-efficiency production inference. You will own system-level architecture, lead multi-quarter initiatives, and partner across engineering to influence department-wide technical strategy while establishing robust processes and mentoring others. What You'll Do: - Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems, aligning with team and department OKRs and KPIs. - Architect System-Level Solutions: Own architecture for complex ML products and design scalable frameworks for massive data mining and optimized real-time inference across GPU/CPU clusters. - Drive Cross-Functional Execution: Lead multi-person projects across teams and influence partner roadmaps to solve shared technical challenges. - Elevate Engineering Excellence: Establish standards for ML system design, code quality, testing, deployment, and incident response planning. - Operate as a Generalist Expert: Apply deep learning, representation learning, active learning, and generative AI to complex problems and unblock teams facing novel challenges. - Mentor and Lead: Coach engineers, lead architectural reviews, and contribute to engineering culture through documentation and technical talks. What We're Looking For (Must-Haves): - BS in Computer Science, Machine Learning, or related field (or equivalent practical experience) - 8+ years of hands-on ML engineering experience with large-scale ML systems - Experience with multimodal foundation models in production systems (camera, LiDAR, radar, text) - Demonstrated technical leadership across multi-quarter, multi-person initiatives - Expert proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX) - Strong software engineering fundamentals including system design, CI/CD, and containerization - Broad ML experience across training, architectures, evaluation, and large-scale deployment - Experience deploying ML models in cloud environments (AWS, GCP, or Azure) with latency and throughput optimization - Proven mentorship and cross-team collaboration skills Bonus Points (Nice-to-Haves): - MS or PhD in Computer Science, Machine Learning, or related field - Background in autonomous driving, robotics, or real-time decision-making systems - Experience with large-scale ML data mining, active learning loops, and contrastive/representation learning - Familiarity with multimodal learning, sensor fusion, or large foundation models - Experience with model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms - Experience leading severity reviews or incident response planning for mission-critical ML platforms Work Arrangement & Compensation: - Hybrid schedule with in-office collaboration in Boston, Pittsburgh, or Las Vegas, or fully remote - Base salary range: $205,000—$272,500 USD - Eligible for additional compensation such as bonus or company equity - Benefits may include medical, dental, vision, 401k with company match, health savings accounts, life insurance, pet insurance, and more