About The Role

Our software team is growing and we are looking for a talented engineer to join our agile, world-class team. In this role you will develop autonomous behaviors for humanoid robots to interact with the world around it. You will work closely with state estimation, navigation, and controls teams to execute behaviors aimed at solving challenging problems in real-world deployments.

About The Work

• Design, implement, test, and deploy autonomous behaviors for humanoid robots
• Prototype autonomous behaviors in simulation and execute on robot hardware
• Develop algorithms robust to environmental uncertainty and imperfect state estimation
• Implement performance tests for evaluating the reliability of robot behaviors
• Contribute to the software architecture and design of the autonomy stack
• Collaborate with members of the autonomy teams to solve complex cross functional problems
• Engineer high quality software that is well tested, reliable and maintainable

About You

• Industry experience deploying mobile manipulation robots in real world applications
• Experience developing manipulation algorithms on high-DOF robots
• Familiarity with behavior trees, finite state machines, or similar behavior management and execution systems
• Experience with perception and scene understanding especially as it pertains to manipulation
• Strong robotics fundamentals, including kinematics, dynamics, sensing, and control
• Experience using simulation tools such as Isaac Sim / Mujoco / Drake / gazebo or similar
• Experience with automated testing for simulation
• Strong debugging skills; the ability to identify and diagnose complex issues that arise within robotics
• Strong software experience in modern C++ and Python

Bonus Qualifications

• Experience working with humanoid (or similar) robots
• Experience leveraging machine learning to improve grasp planning and object manipulation
• Experience in classical robotics motion planning and trajectory optimization algorithms
• MS or Ph.D. in robotics, computer science, or related field or have equivalent industry experience
• Publications in your field (RSS, ICRA, IROS preferred)

We are open to remote candidates, but a prefer this role to be hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.  

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The hardware sensing team is responsible for the benchmarking, characterizing, and nomination and integration of all sensors. We work cross functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements, perception requirements, and that it is integrable and reliable in Ford’s series vehicles. We are expected to understand sensing from a first principle approach and to ensure those principles are designable and manufacturable.  We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members of the team are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding and comfortability of concepts across many disciplines–from hardware and software.

What you’ll do: 

• Lead technical development of radar or lidar sensing systems from early concept, benchmarking, and sourcing through production launch
• Define sensor performance targets, requirements, evaluation criteria, and validation plans based on vehicle, perception, and ODD needs
• Drive sensor benchmarking and technical down-selection across candidate suppliers and technologies
• Lead supplier technical engagement, including requirements reviews, data reviews, architecture discussions, issue resolution, and design maturity assessments
• Guide architecture and tradeoff decisions related to sensing performance, environmental robustness, packaging, thermal constraints, power, diagnostics, manufacturability, and cost
• Work cross-functionally with systems, perception, firmware, validation, vehicle integration, manufacturing, and quality teams to ensure the sensor meets downstream functional and program needs
• Review test data from supplier, bench, track, and vehicle testing; identify performance gaps; determine root cause; and drive corrective actions
• Assess whether supplier evidence is technically credible by reviewing test conditions, assumptions, filtering, sample quality, boundary cases, repeatability, and alignment to sensor physics and system requirements
• Lead technical reviews and challenge unsupported claims, weak correlation, incomplete validation, and conclusions that do not match observed data or first-principles behavior
• Establish technical plans, milestones, risks, and mitigation strategies to keep sensor programs on track toward nomination and launch
• Communicate technical status, open issues, and tradeoffs clearly to engineering leadership and cross-functional partners

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)
• 8+ years of experience in automotive sensing, with deep hands-on expertise in either radar or lidar and demonstrated technical leadership on complex hardware programs
• Strong first-principles understanding of the relevant sensing modality:
  • Radar: RF fundamentals, range/Doppler/angle estimation, resolution, interference, multipath, ghosting, calibration, synchronization, and environmental effects
  • Lidar: time-of-flight or FMCW fundamentals, ranging accuracy, reflectivity effects, point cloud quality, contamination, weather impacts, optical alignment, calibration, and environmental robustness
• Strong scripting and analysis capability in python, including hands-on use of NumPy, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows
• Ability to work directly with sensor data and debug artifacts, including supplier logs, raw captures, decoded outputs, and vehicle test datasets, and determine whether the data is complete, valid, and physically credible
• Practical experience with day-to-day engineering tools such as Wireshark/PCAP analysis, CAN tools (CANoe/CANalyzer or similar), ROS/rosbag or equivalent logging frameworks, point cloud or radar visualization tools, and common automotive data interfaces such as CAN, CAN FD, and automotive Ethernet
• Ability to independently judge whether supplier test results are correct by evaluating test setup, calibration state, ground truth method, statistical significance, repeatability, boundary conditions, applied filters, KPI definitions, and consistency with known sensor behavior
• Ability to lead and critically assess technical design reviews (TDRs) by identifying weak assumptions, incomplete validation, inconsistent requirements traceability, misleading metrics, and conclusions that are not supported by the underlying data
• Experience translating system and perception needs into sensor requirements, validation methods, and supplier deliverables
• Experience working across hardware, firmware, systems, perception, validation, manufacturing, and supplier teams to drive root cause and resolution
• Strong technical judgment and communication skills, with the ability to make and defend tradeoffs across performance, cost, timing, integration, and reliability

Nice to have: 

• Master’s degree or PhD in Electrical Engineering, Physics, Robotics, Computer Science, or a related field
• Experience leading supplier nomination, sourcing, or technical selection for radar or lidar hardware
• Experience bringing radar or lidar systems into automotive production
• Familiarity with DV/PV, DFMEA, APQP, PPAP, functional safety, automotive quality processes, and production release expectations
• Working knowledge of perception, tracking, calibration, and downstream use of radar or lidar data in automated driving systems
• Experience supporting multiple vehicle platforms or series-production programs

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $191,920 - $287,880 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The hardware sensing team is responsible for the benchmarking, characterizing, and nomination and integration of all sensors. We work cross functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements, perception requirements, and that it is integrable and reliable in Ford’s series vehicles. We are expected to understand sensing from a first principle approach and to ensure those principles are designable and manufacturable.  We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members of the team are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding and comfortability of concepts across many disciplines–from hardware and software.

What you’ll do: 

• Lead technical development of radar or lidar sensing systems from early concept, benchmarking, and sourcing through production launch
• Define sensor performance targets, requirements, evaluation criteria, and validation plans based on vehicle, perception, and ODD needs
• Drive sensor benchmarking and technical down-selection across candidate suppliers and technologies
• Lead supplier technical engagement, including requirements reviews, data reviews, architecture discussions, issue resolution, and design maturity assessments
• Guide architecture and tradeoff decisions related to sensing performance, environmental robustness, packaging, thermal constraints, power, diagnostics, manufacturability, and cost
• Work cross-functionally with systems, perception, firmware, validation, vehicle integration, manufacturing, and quality teams to ensure the sensor meets downstream functional and program needs
• Review test data from supplier, bench, track, and vehicle testing; identify performance gaps; determine root cause; and drive corrective actions
• Assess whether supplier evidence is technically credible by reviewing test conditions, assumptions, filtering, sample quality, boundary cases, repeatability, and alignment to sensor physics and system requirements
• Lead technical reviews and challenge unsupported claims, weak correlation, incomplete validation, and conclusions that do not match observed data or first-principles behavior
• Establish technical plans, milestones, risks, and mitigation strategies to keep sensor programs on track toward nomination and launch
• Communicate technical status, open issues, and tradeoffs clearly to engineering leadership and cross-functional partners

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)
• 8+ years of experience in automotive sensing, with deep hands-on expertise in either radar or lidar and demonstrated technical leadership on complex hardware programs
• Strong first-principles understanding of the relevant sensing modality:
  • Radar: RF fundamentals, range/Doppler/angle estimation, resolution, interference, multipath, ghosting, calibration, synchronization, and environmental effects
  • Lidar: time-of-flight or FMCW fundamentals, ranging accuracy, reflectivity effects, point cloud quality, contamination, weather impacts, optical alignment, calibration, and environmental robustness
• Strong scripting and analysis capability in python, including hands-on use of NumPy, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows
• Ability to work directly with sensor data and debug artifacts, including supplier logs, raw captures, decoded outputs, and vehicle test datasets, and determine whether the data is complete, valid, and physically credible
• Practical experience with day-to-day engineering tools such as Wireshark/PCAP analysis, CAN tools (CANoe/CANalyzer or similar), ROS/rosbag or equivalent logging frameworks, point cloud or radar visualization tools, and common automotive data interfaces such as CAN, CAN FD, and automotive Ethernet
• Ability to independently judge whether supplier test results are correct by evaluating test setup, calibration state, ground truth method, statistical significance, repeatability, boundary conditions, applied filters, KPI definitions, and consistency with known sensor behavior
• Ability to lead and critically assess technical design reviews (TDRs) by identifying weak assumptions, incomplete validation, inconsistent requirements traceability, misleading metrics, and conclusions that are not supported by the underlying data
• Experience translating system and perception needs into sensor requirements, validation methods, and supplier deliverables
• Experience working across hardware, firmware, systems, perception, validation, manufacturing, and supplier teams to drive root cause and resolution
• Strong technical judgment and communication skills, with the ability to make and defend tradeoffs across performance, cost, timing, integration, and reliability

Nice to have: 

• Master’s degree or PhD in Electrical Engineering, Physics, Robotics, Computer Science, or a related field
• Experience leading supplier nomination, sourcing, or technical selection for radar or lidar hardware
• Experience bringing radar or lidar systems into automotive production
• Familiarity with DV/PV, DFMEA, APQP, PPAP, functional safety, automotive quality processes, and production release expectations
• Working knowledge of perception, tracking, calibration, and downstream use of radar or lidar data in automated driving systems
• Experience supporting multiple vehicle platforms or series-production programs

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $191,920 - $287,880 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The hardware sensing team is responsible for the benchmarking, characterizing, and nomination and integration of all sensors. We work cross functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements, perception requirements, and that it is integrable and reliable in Ford’s series vehicles. We are expected to understand sensing from a first principle approach and to ensure those principles are designable and manufacturable.  We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members of the team are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding and comfortability of concepts across many disciplines–from hardware and software.

What you’ll do: 

• Test Strategy & Compliance: Lead the development of Design Verification (DV) and Production Validation (PV) plans. Ensure all hardware-level testing aligns with Ford automotive standards (CETP) and international standards such as ISO 16750 and ISO 26262
• Sensor Validation: Execute and oversee comprehensive testing for sensing modalities including Camera (optics/image quality), Radar (RF performance), Lidar (point cloud accuracy), IMU, and GPS/GNSS
• Reliability Engineering: Conduct environmental and mechanical stress testing (thermal cycling, vibration/shock, humidity, ingress protection, and EMC/EMI) to determine Mean Time To Failure (MTTF) and ensure 10-year/150,000-mile durability
• Vendor & Lab Management: Act as the primary technical point of contact for Tier 1 suppliers and external test labs. Manage the statement of work (SOW), audit lab setups, and ensure external testing is executed to Ford’s precision requirements
• Test Automation & Scripting: Develop and maintain automated test scripts (Python, MATLAB, or Bash) to streamline data acquisition, sensor calibration, and post-processing of large datasets
• Data Analysis & Reporting: Review and interpret complex test results. Perform root cause analysis (RCA) on hardware failures and work closely with design teams to implement hardware revisions
• Cross-Functional Leadership: Mentor junior engineers and collaborate with Systems Engineering, Perception Teams, and Manufacturing to ensure sensor hardware integrates seamlessly into the vehicle platform

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Minimum of seven years of professional experience in hardware testing or reliability engineering.
• Extensive experience testing sensing technologies such as cameras, radar, lidar
• Proficiency in writing scripts using Python or similar languages for data analysis and automation.
• Demonstrated ability to manage projects involving external laboratories and global suppliers.
• Expertise in applying standardized automotive engineering test procedures for environmental and mechanical durability.
• Strong analytical skills for identifying the root cause of hardware malfunctions in automotive electronics.

Nice to have: 

• Direct experience in hardware product development for automotive with a focus on sensing products
• Direct experience/exposure to product development of silicon products such as transceivers, imagers, MCUs
• Manufacturing or industrialization of electronics products

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $160,000 - $240,000 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Company Name: Hellbender Inc.

Job Title: Robotics Engineering Internship

Department: Engineering

Report to: Engineering Manager 

Who we are:

Hellbender Inc. is a Pennsylvania Benefit Corporation who partners with innovators to mature their Artificial Intelligence enabled computing sensors and produce their solutions onshore at prototype to high volumes.

Hellbender is intentionally forming an inclusive work environment and is committed to uplifting the historically marginalized identities including veterans, women, trans and non-white races in our community and industry.        

Job Summary: 

At Hellbender, you will have the opportunity and responsibility to generate innovative solutions
to address unique issues on a variety of real world problems. As an intern, you will have the
same autonomy as our junior engineers and the mentorship of our senior staff. Our program is
designed to teach you the full product development life cycle and the work will take you back
and forth from the white board to the automated manufacturing line. The coding will consist of
Real-Time/Object Oriented C, C++, and Python development in an embedded Linux
environment.

Eligibility Requirements
An ideal candidate would have prior internship experience at a manufacturing or engineering
based organization. We accept college masters and PhD level students.

Please note that this is a full time, on-site position.

• 3.0 or higher cumulative GPA preferred
• Enrolled in an accredited U.S. college or university
• Classification as a graduate student (master’s or doctoral level)
• Must be authorized to work in the U.S.
• Must be willing to work onsite

Essential Duties and Responsibilities:

• Working on embedded platform software in a Linux-based environment
• Writing event-driven and asynchronous applications primarily in C, C++ and Python
• Writing software that communicates with and controls other devices over interfaces
  including CAN, UART, I2C, SPI and others
• Using oscilloscopes, protocol analyzers, multimeters, and other tools for electronic
  diagnostics
• Define requirements for specific functionality and coordinate with hardware, software
  manufacturing teams
• Demonstrate proficiency in data analysis, programming, and software engineering

Work Location: UPARC Pittsburgh

Opportunity for advancement: 

Hellbender is a growing business and follows a policy that prioritizes internal promotions. As new positions are created new opportunities for advancement will be created as well.

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 Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. 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, safety monitoring, etc., 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.

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 Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. 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, safety monitoring, etc., 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.

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 Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. 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, safety monitoring, etc., 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.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

Mission Summary:

• Lead the design, development, and integration of complex electrical and mechanical systems for autonomous vehicles, ensuring they meet rigorous performance, safety, and reliability standards.
• Architect, analyze, and optimize vehicle electrical and networking systems (Automotive Ethernet, CAN) to enhance data throughput, fault tolerance, and system scalability.
• Spearhead the diagnosis and resolution of complex, intermittent system failures using advanced debugging tools (e.g., high-speed oscilloscopes, spectrum analyzers, logic analyzers) and sophisticated PC-based diagnostic and simulation software.
• Mentor junior engineers on best practices for system triage, troubleshooting, repair, and validation.
• Develop and execute comprehensive integration test plans for new vehicle features and subsystems, coordinating efforts across multiple engineering disciplines and external partners.
• Author and maintain high-level technical documentation for system architectures, design requirements, and validation procedures.
  
  

What we're looking for:

• Expert-level knowledge of vehicle electrical and networking systems (CAN, LIN, Ethernet, etc.) with a deep understanding of communication protocols and their limitations.
• Proven track record of success in root-cause analysis, systematic issue isolation, and resolution for complex hardware-software integration problems.
• Extensive experience with advanced Linux terminal troubleshooting, including scripting and low-level system diagnostics.
• Deep understanding of computer system architecture, including embedded systems, processing units, and networking hardware.
• Demonstrated ability to author and maintain highly technical documentation, including design specifications, test reports, and system validation plans.
• Exceptional problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.
• Excellent communication and interpersonal skills to effectively lead cross-functional teams and collaborate with external suppliers and partners.
• Extensive experience with various sensors, including cameras, LiDAR, and RADAR, and an understanding of their integration challenges.
• Master's degree or equivalent in Electrical, Mechanical, or Systems Engineering, or 10+ years of relevant experience in a senior-level role.
  
  

Preferred, but not required:

• Professional proficiency in programming languages such as Python or C++ for scripting, automation, and data analysis.
• Experience with advanced issue-tracking and project management platforms (e.g., JIRA, Polarion, Confluence), including dashboard creation and workflow optimization.
• Working knowledge of functional safety standards (e.g., ISO 26262) and their application in autonomous systems.

This role is hybrid from our Pittsburgh office. It requires in-office days each week.

About the Role

We are looking for a Staff Robotics Software Engineer (Tech Lead) to lead the design and development of robot behaviors that expand and generalize our humanoid robot’s capabilities. In this role, you will own behavior design end-to-end, from high-level task logic and system design down to on-robot validation and deployment. You will work at the intersection of behavior planning, motion planning, object perception, and manipulation, developing new autonomy capabilities and pushing the robot into new classes of tasks. We are looking for a hands-on technical leader who can set technical direction and wants to stay close to the robot: writing code, running experiments, debugging logs, working with hardware, and mentoring other engineers by building alongside them.

Key Responsibilities

• Own the design, implementation, and validation of complex humanoid robot behaviors.
• Lead behavior planning and execution design, including task decomposition, control flow, recovery, and failure handling.
• Build new autonomy capabilities that expand what the robot can reliably do in the real world.
• Develop and evaluate manipulation strategies for new tasks, objects, workflows, and customer environments.
• Integrate robot behaviors with motion planning, controls, object perception, estimation, and hardware systems.
• Train, evaluate, and integrate learned policies into hybrid learned/classical execution workflows.
• Integrate new end effectors, tools, sensors, and other hardware capabilities into the behavior stack.
• Debug complex system-level failures using logs, replay, metrics, simulation, and on-robot experimentation.
• Mentor engineers through design reviews, code reviews, debugging, and hands-on technical guidance.
• Help set technical direction and best practices for building robust, composable, reusable, and generalizable robot behaviors.

About You

• B.S., M.S., or Ph.D. in Robotics, Computer Science, or a related engineering field.
• 8+ years of professional experience developing robotics software, autonomy systems, robot behaviors, or related real-world robotic capabilities.
• Demonstrated experience as a tech lead or senior technical owner for complex robotics projects.
• Proficient in Python and C++, and comfortable contributing to large, long-lived codebases.
• Experience with behavior trees, state machines, task planners, hierarchical planning, or similar behavior-planning frameworks.
• Strong system-level understanding of how motion planning, object perception, controls, estimation, and hardware interact on real robots.
• Experience working with complex algorithms and data pipelines, with an ability to optimize for performance, robustness, and scalability.
• Experience collaborating closely with perception, planning, controls, hardware, product, or field teams.
• Strong ownership mindset with a focus on robustness, generalization, and real-world reliability.

Bonus Qualifications

• Experience developing manipulation strategies for complex or unstructured environments.
• Experience with learned robot skills, including imitation learning, reinforcement learning, or hybrid learned/classical execution strategies.
• Experience deploying and supporting autonomous robots in real customer environments.

This is a hybrid role based out of one of our Salem, OR, Pittsburgh, PA, or Fremont, CA offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

About the Role

We are looking for a Staff Robotics Software Engineer to join our Skills team, focusing on object perception for robot manipulation. This technical leadership role is deeply rooted in production robotics, where reliability, performance, and system behavior matter most. You will focus on integrating, adapting, and operationalizing perception systems within a full robotic stack, ensuring they perform robustly on real hardware in real environments.

In this high-impact role, you will act as a key decision-maker within the perception and skills stack, helping define system architecture, design principles, and technical direction across how perception connects to planning, control, and execution. You will shape how these systems come together end-to-end, influencing both current execution performance and the long-term scalability of the platform.

You will also work closely with AI/ML teams, evaluating and incorporating both learned and classical approaches, while driving the engineering decisions that turn models and algorithms into reliable, production-grade robot behavior.

About the Work

• Own object perception performance on the robot, from sensors through runtime behavior integration
• Lead the design, implementation, and deployment of perception pipelines for manipulation, including object pose estimation, depth reasoning, and scene understanding
• Work hands-on with real robots to debug, tune, and harden perception systems under real-world variability
• Collaborate with AI/ML teams to evaluate, integrate, train, and fine-tune perception models
• Explore and integrate off-the-shelf perception solutions and libraries where they meet performance and reliability needs
• Combine learned models with classical CV, geometry, and task structure to meet system-level requirements
• Define interfaces and contracts between perception, behaviors, and task planning to ensure reliable execution
• Build tools and workflows to evaluate perception performance across datasets, simulation, and hardware
• Help set technical direction and best practices for building robust, production-grade perception systems that are reliable, debuggable, and scalable in real-world robotic environments

About You

• B.S., M.S., or Ph.D. in Robotics, Computer Science, or a related engineering field
• 8+ years of professional experience building object perception systems for real robotic platforms
• Demonstrated experience as a tech lead or senior technical owner for complex robotics projects
• Experience working across learned models and classical perception approaches
• Experience training, fine-tuning, and evaluating perception models
• Strong experience writing production-quality C++ and Python code
• Hands-on experience with monocular vision, stereo vision, RGB-D sensing, or depth reconstruction
• Experience with perception libraries (OpenCV, Open3D, PCL, ROS perception, NumPy, scikit-image)
• You love solving hard perception problems, but your real passion is seeing those solutions work on a robot in the real world and having an impact
• You’re excited to work on hardware
• You enjoy debugging, testing, and iterating quickly in simulation and on the real robot

You Might Also Have

• Solid understanding of spatial reasoning 
• Demonstrated ability to apply object perception model outputs (detection, segmentation, pose estimation) in manipulation pipelines
• Experience with structured 3D estimation (plane fitting, normal estimation, voxel maps, etc)

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

Mission Summary:

The Senior Engineer Team Lead is responsible for the validation of the autonomous vehicle stack with a primary emphasis on the interface between software and physical hardware. This role leads the development and execution of Hardware-in-the-Loop (HIL) testing strategies to ensure that perception, planning, and control algorithms interact safely and reliably with vehicle sensors, actuators, and ECUs.

You will be the technical authority for HIL bench architecture and hardware-software integration, ensuring that the "brain" of the vehicle commands the physical "body" with millisecond precision and fail-safe reliability.

Essential Duties:

• HIL Strategy & Architecture: Lead the design, setup, and maintenance of high-fidelity HIL test benches (e.g., dSPACE, NI, or Speedgoat). Define the hardware-software mapping required to simulate real-world vehicle dynamics.
• Hardware-Software Integration: Own the validation of the Drive-by-Wire (DBW) system, ensuring steering, braking, and acceleration commands meet safety-critical latency and accuracy requirements.
• Fault Injection & Robustness: Design and execute complex hardware fault-injection campaigns (e.g., sensor signal loss, CAN bus flooding, power interrupts) to validate system-level safety monitors.
• Communication Protocol Expert: Direct the testing of automotive communication networks, including CAN, CAN-FD, Automotive Ethernet, and LIN, using tools like Vector CANoe/CANalyzer.
• Multi-Modal Validation: While focusing on hardware, maintain oversight of SIL and closed-course testing to ensure HIL results correlate with virtual and physical track performance.
• Mechatronic Debugging: Lead root-cause analysis for complex electromechanical issues, utilizing oscilloscopes, multimeters, and logic analyzers to debug signal integrity and power distribution.
• Tooling & Automation: Architect Python-based automation frameworks for HIL regression suites, reducing manual bench time and increasing test coverage.
• Safety Compliance: Act as a lead reviewer for ISO 26262 functional safety requirements, specifically focusing on Hardware-Software Interface (HSI) specifications.
  
  

Qualifications:

• Education: Bachelor’s or Master’s degree in Electrical Engineering, Mechatronics, Mechanical Engineering, or Robotics.
• Experience: 5+ years in Systems/Hardware testing, with at least 3 years focused on HIL simulation within the automotive or aerospace industry.
• Technical Mastery:
• Hardware: Expert knowledge of ECUs, sensors (Lidar/Radar/Camera), and mechatronic actuators.
• Simulators: Proven experience configuring real-time simulation environments (e.g., dSPACE ControlDesk, NI VeriStand, or IPG CarMaker).
• Scripting: Expert proficiency in Python for test automation and Matlab/Simulink for plant model integration.
• Domain Expertise:
• Deep understanding of automotive electrical architectures and power management.
• Experience with sensor calibration and synchronization across hardware interfaces.
• Familiarity with SOTIF (ISO 21448) and how hardware limitations impact autonomous functionality.
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the team member is regularly exposed to outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The noise level in the environment is low to moderate.

Motional AD LLC is an Equal Employment Opportunity employer, and we welcome all qualified applicants.  All applicants will receive impartial consideration regarding race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation, or another legally protected status.  Motional AD LLC is a Drug-free workplace.

This role is based in our Pittsburgh office and requires in-office days each week.

We are looking for a Lead RTL Design Engineer to own microarchitecture definition and RTL implementation across the dataflow execution fabric, memory subsystem, on-chip interconnect/NoC, low-power logic, and standard peripheral IP (RiscV, NVM, I2S, I2C) integration. You will work from architecture spec through synthesis-ready RTL, collaborating with architects, microarchitects, DV leads, physical design, and firmware teams to tape out an industry leading power-efficient SoC.

This is a unique opportunity to be a part of a newly formed HW engineering org and have an influence on our products and processes as we move from the initial stages of product development to market release and scaled volume production.  Join our team and help us shape the future of computing at the edge and beyond!

Key Responsibilities 

• Microarchitecture definition (core focus): Own the design and definition of processor and compute-unit microarchitecture, including dataflow pipelines, execution units, and interfaces. Set performance, power, and area targets, and guide the team toward achieving them.
• On-chip interconnects and system integration: Define and drive the design of on-chip networks and data movement across the fabric, balancing performance, scalability, and implementation constraints in collaboration with physical design.
• Memory subsystem & system architecture: Define the interface to the memory subsystem, including data movement, ordering, and synchronization behavior, ensuring a clean and scalable model for software and future system expansion.
• Reconfiguration and execution model: Lead the architecture of configuration, scheduling, and execution of workloads on the fabric, including multi-kernel support and interaction with host systems.
• Power management and low-power design: Drive power architecture across the design, including clocking, reset, power domains, and low-power strategies to meet aggressive energy and efficiency goals.
• HW/SW co-design: Collaborate closely with compiler and software teams to define the hardware execution model, ensuring efficient mapping of workloads onto the architecture.

Specifications, Documentations and Reviews: Author and own uArch specification documents for assigned blocks; drive design reviews with architecture, compiler, DV, and physical design stakeholders.

• Mentoring and process improvement: Mentor senior and junior RTL engineers; review RTL, flag microarchitecture risks, and enforce coding style and lint-clean standards across the team.
• Driving PPA Metrics: Participate in PPA analysis loops: synthesize blocks regularly, review area/timing/power reports, and make data-driven tradeoffs against performance and feature requirements.
• DV Collaboration: Collaborate with DV leads to define/review verification plans; provide directed test scenarios for graph execution corner cases, back-pressure conditions, and power state transitions.
• Silicon Bring-up: Support silicon bring-up: contribute scan/ATPG guidelines, review DFT insertion, and provide RTL-level debug assistance during lab validation.

Required Qualifications & Experience

• 8+ years of RTL design experience with tape-out ownership of dataflow based design, on chip networks, memory subsystems  or peripheral integration on a processor or accelerator SoC.
• Deep proficiency in SystemVerilog for RTL — synthesis-clean, lint-clean, timing-aware; able to design complex state machines, arbiters, token flow controllers, and datapath logic from scratch.
• Solid understanding of parallel execution models: dataflow, SIMD, or systolic array architectures; familiarity with the hardware challenges of token-based firing-rule evaluation and producer-consumer synchronization.
• Hands-on experience with on-chip memory design: SRAM wrappers, scratchpad/TCM, banking, and memory-mapped register interfaces.
• Experience with low-power RTL techniques: UPF-driven flows, clock gating, power domains, retention registers, and AON wakeup logic.
• Familiarity with at least one standard on-chip bus protocol (AXI, AHB, APB, TileLink, or NoC equivalent) at the RTL implementation level.
• Experience taking RTL through synthesis and timing closure; ability to read and act on SDC constraints, STA reports, and synthesis QoR summaries.
• Strong written communication skills; able to produce uArch specs and design review material independently.
• Experience with memory compiler toolchains

Desired Qualifications & Experience Requirements 

• Prior RTL ownership of a dataflow engine, neural processing unit (NPU), or streaming DSP architecture with explicit producer-consumer token management.
• Experience collaborating with compiler or graph-optimization teams to co-design hardware execution models and graph IR representations.
• Familiarity with NVM controller RTL (MRAM, RRAM) including ECC, program/erase sequencing, and model weight storage use cases.
• Experience with IoT-class power budgets (sub-10 mW active, sub-100 µW standby) and the RTL design choices they necessitate.
• Familiarity with functional safety standards (ISO 26262, IEC 61508) as applied to execution fabric error detection and power domain isolation.
• Exposure to AI framework graph formats (ONNX, TFLite) and understanding of how graph compilation maps to hardware execution primitives.
• Tape-out credits on an edge-AI, IoT, or wearable SoC at 12nm or below.
• Experience with formal verification of flow-control logic, deadlock freedom, or bus protocol compliance.

We offer a competitive salary for this role, generally ranging from $160,000 to $250,000, along with meaningful equity and comprehensive benefits. The final compensation package will be based on your experience and location, with some flexibility to ensure we align with the right candidate.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

Mission Summary:

Our Vehicle Platform Components team is seeking a highly motivated Senior Engineer to assume ownership of the development and integration of the autonomous vehicle’s vision sensors. This position serves as the primary technical owner for the development, validation, and production readiness of our vision sensors. The incumbent will ensure that sensors adhere to all functional requirements and quality standards, and will support sensor delivery to satisfy all performance, cost, and timing objectives.

Key Responsibilities:

• Develop and manage component-level technical requirements throughout the program development lifecycle.
• Lead technical collaboration with component suppliers, serving as the internal technical expert for the component.
• Ensure all components comply with specifications for performance KPIs, safety, and reliability.
• Guarantee that components adhere to relevant industry standards and regulatory requirements.
• Collaborate with Design Release Engineers to ensure components meet the overall product's program targets and goals.
• Collaborate with Systems Engineers to confirm that component requirements satisfy system needs and that selected components integrate seamlessly into the overall system architecture.
• Responsible for validating component functionality through hands-on testing conducted at both the bench and vehicle levels.
• Lead issue resolution with suppliers and internal cross-functional teams in a timely and effective manner.

What We’re Looking For:

• 7+ years of experience in automotive component design, development and integration.
• Bachelor’s or Master’s degree in Electrical Engineering, Electronics Technology, Optoelectronics (or a related field).
• Demonstrated knowledge of optical systems, encompassing the construction and design of camera components.
• Experience with machine vision camera design, development and integration.
• Understanding of high-throughput Image Signal Processing (ISP) pipeline design and implementation.
• Experience with automotive communication protocols including CAN, CAN-FD, Ethernet, GMSL, and FPD-Link.
• Proficiency in Linux, including the ability to develop scripts (e.g., Python, C++) for testing, validation, and interaction with camera hardware.
• Familiarity with NVIDIA DRIVE AGX Orin / Thor architecture and developer kits.
• Experience with lab equipment, including power supplies, oscilloscopes, multimeters, and function generators.
• Proficiency in automotive diagnostic tools, including Vector tools (CANoe, CANape, vFlash).
• Experience with automotive environmental, EMI, and shock/vibration testing.
• Experience in root-cause analysis, with a focus on utilizing AV / ADAS vehicle logs to pinpoint sensor impairments that negatively affect autonomous system performance.
• Familiarity with automotive components validation documentation and procedures, such as DVP&R, DFMEA and PFMEA.
• Experience with requirement compliance, issue-tracking and task management software platforms such as JIRA, Polarion, Confluence, etc.
• Demonstrated experience collaborating with an automotive Tier-1 supplier on the technical development of electronic components.
• Understanding of vehicle integration, packaging, and functional safety standards (ISO 26262)
  
  

Bonus Points:

• Prior experience in automotive vision sensor hardware and software integration or ADAS technologies.
• Prior experience in an autonomous vehicle or robotics company.

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 Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

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.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

Mission Summary:

Our newly formed Design Release Engineering team, within the Vehicle Platform Engineering group, is seeking a highly motivated Staff Engineer to own the design release and integration of  vehicle control and interface subsystems. This role serves as the primary technical authority for the end-to-end design, release, validation, and production readiness of key vehicle modules, including core systems such as Autonomous Emergency Braking (AEB), Vehicle Interface Controllers (VIC), Cabin Monitoring Systems, and Human-Machine Interface (HMI) hardware. You will ensure robust technical execution, manage supplier and cross-functional alignment, and drive hardware delivery that meets all performance, cost, and timing objectives.

What You’ll Be Doing:

• Own the complete design release of critical vehicle system hardware, including the mechanical mounting, alignment, thermal management, electrical interface, and vehicle network integration.
• Drive technical execution for the full product lifecycle, from concept and architecture definition to sustaining engineering and continuous improvement.
• Oversee the generation and release of all engineering documentation, including models and drawings, Bills of Material (BOM), specifications, and test reports, ensuring alignment with vehicle-level design.
• Collaborate closely with the base vehicle supplier (OEM partner) to ensure seamless mechanical, electrical, and network integration of the vehicle controllers and interface modules into the base vehicle architecture, managing shared Interface Control Documents (ICDs).
• Define and maintain the Design Verification Plan & Report (DVP&R), ensuring successful validation against system performance targets.
• Lead the Engineering Change (ECN) process for all assigned vehicle system modules, ensuring traceability, cost impact analysis, version control, and full cross-functional buy-in.
• Act as the primary technical and program interface to suppliers (Tier 1 and Tier 2), tracking part maturity through DV, PV, and PPAP phases to ensure tooling and delivery readiness.
• Build strong partnerships across the Systems Engineering, Autonomy, Software Infrastructure, Quality, and Vehicle Integration teams to ensure seamless hardware integration and manufacturability (DFM/DFA).
• Lead technical program reviews and design readiness assessments, proactively developing risk mitigation plans to ensure compute hardware maturity aligns with program milestones and build events.
• Provide regular, concise updates to technical leadership on design maturity, validation progress, open issues, and timely closure metrics.
  
  

What We’re Looking For:

• 8+ years of experience in automotive hardware design and release engineering, with direct ownership of ADAS/Active Safety hardware, low-level vehicle controllers, or interior electronic modules preferred.
• Bachelor’s or Master’s degree in Electrical, Mechanical, Computer, or Systems Engineering (or a related field).
• Deep technical understanding of core vehicle control architectures (e.g., AEB and VIC) and automotive network topologies (e.g., CAN-FD, automotive ethernet).
• Technical knowledge of interior electronics and cockpit integration, including HMI ECUs/displays, cabin monitoring sensors, and their associated high-speed video/data protocols (e.g., GMSL, FPD-Link).
• Fundamental knowledge of validation documentation and processes, including DVP&R, DFMEA, and PFMEA.
• Expert-level experience with the manufacturing BOM and ECN processes, and a proven ability to manage technical discussions with external suppliers.
• Familiarity with CAD systems (e.g., NX, CATIA), Product Lifecycle Management (PLM) systems (including requirement management tools such as Polarion), and engineering release workflows.
• Strong understanding of vehicle integration, packaging, and functional safety standards (ISO 26262).
• Proven ability to lead complex initiatives, manage cross-functional teams, and execute to aggressive program timelines with minimal oversight.
  
  

Bonus Points:

• Experience with advanced in-vehicle prototypes and benchtop systems.
• Proven track record of driving goal-level impact across multiple teams or subsystems.
• Prior experience in a fast-growing autonomous vehicle or robotics company.
  
  

This role is based in our Pittsburgh office and requires in-office days each week.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

Mission Summary:

Our newly formed Design Release Engineering team, within the Vehicle Platform Engineering group, is seeking a highly motivated Staff Engineer to own the design release and integration of our autonomous vehicle’s compute and connectivity subsystem. This role serves as the primary technical authority for the end-to-end design, release, validation, and production readiness of our high-performance compute hardware and associated controllers. You will ensure robust technical execution, manage supplier and cross-functional alignment, and drive hardware delivery that meets all performance, cost, and timing objectives.

What You’ll Be Doing:

• Own the complete design release of the high-performance compute and connectivity hardware, including the mechanical mounting, alignment, thermal management, electrical interface, and vehicle network integration.
• Drive technical execution for the full product lifecycle, from concept and architecture definition to sustaining engineering and continuous improvement.
• Oversee the generation and release of all engineering documentation, including models and drawings, Bills of Material (BOM), specifications, and test reports, ensuring alignment with vehicle-level design.
• Define and maintain the Design Verification Plan & Report (DVP&R), ensuring successful validation against system performance targets.
• Lead the Engineering Change (ECN) process for compute and connectivity hardware, ensuring traceability, cost impact analysis, version control, and full cross-functional buy-in.
• Act as the primary technical and program interface to suppliers (Tier 1 and Tier 2), tracking part maturity through DV, PV, and PPAP phases to ensure tooling and delivery readiness.
• Build strong partnerships across the Systems Engineering, Autonomy, Software Infrastructure, Quality, and Vehicle Integration teams to ensure seamless hardware integration and manufacturability (DFM/DFA).
• Lead technical program reviews and design readiness assessments, proactively developing risk mitigation plans to ensure compute hardware maturity aligns with program milestones and build events.
• Provide regular, concise updates to technical leadership on design maturity, validation progress, open issues, and timely closure metrics.
  
  

What We’re Looking For:

• 8+ years of experience in automotive hardware design and release engineering, with direct ownership of Domain Controllers, HPCs, or Telematics units.
• Bachelor’s or Master’s degree in Electrical, Mechanical, Computer, or Systems Engineering (or a related field).
• Deep technical understanding of compute architectures, high-speed data buses, and wireless connectivity standards.
• Fundamental knowledge of validation documentation and processes, including DVP&R, DFMEA, and PFMEA.
• Expert-level experience with the manufacturing BOM and ECN processes, and a proven ability to manage technical discussions with external suppliers.
• Familiarity with CAD systems (e.g., NX, CATIA), Product Lifecycle Management (PLM) systems (including requirement management tools such as Polarion), and engineering release workflows.
• Strong understanding of vehicle integration, packaging, and functional safety standards (ISO 26262).
• Proven ability to lead complex initiatives, manage cross-functional teams, and execute to aggressive program timelines with minimal oversight.
  
  

Bonus Points:

• Experience with advanced in-vehicle prototypes and benchtop systems.
• Proven track record of driving goal-level impact across multiple teams or subsystems.
• Prior experience in a fast-growing autonomous vehicle or robotics company.

This role is based in our Pittsburgh office and requires in-office days each week.

Mission Summary:

The Staff Systems Safety Engineer:

• Oversees the development and implementation of engineering safety processes for our autonomous vehicle systems
• Is responsible for reviewing hazards, risk assessments, and ensuring compliance with industry safety standards (ISO 26262, SOTIF, and ASIL).
• Collaborates with cross-functional teams, including software, hardware, and AI engineers, to ensure integration of safety into the design and validation of our AV system
  
  

Essential Duties:

• Ensure and oversee the development and implementation of  system safety processes for autonomous vehicle platforms.
• Ensure hazard analysis and risk assessments (HARA) for AV components and subsystems are conducted.
• Assist in the definition and verification of functional safety requirements in compliance with ISO 26262 and SOTIF (ISO 21448).
• Collaborate with hardware, software, and AI teams to integrate safety measures into perception, decision-making, and control systems.
• Support the development of failure mode and effects analysis (FMEA) and fault tree analysis (FTA) for AV systems.
• Ensure compliance with regulatory and industry safety standards, including SAE J3016, NHTSA, and UNECE WP.29.
• Ensure the development and execution of safety verification and validation plans, including simulation, testing, and real-world driving scenarios.
• Work with certification bodies and regulators to ensure safety case documentation and approval processes.
• Contribute to the development of safety culture within the organization by providing guidance and training
  
  

Qualifications:

Educational Requirements

• Bachelor’s or Master’s degree in Systems Engineering, Electrical Engineering, Computer Science, Mechanical Engineering, or a related field 

Technical / Specialized Knowledge, Skills, Abilities:

• 5+ years industry and 3+ years of experience in safety engineering for automotive, aerospace, or robotics systems.
• Strong knowledge of functional safety standards (ISO 26262, SOTIF, ASIL).
• Knowledge of systems / software engineering standards (INCOSE, ISO15288, ASPICE CMMI)
• Experience with hazard analysis, risk assessment, and safety case development.
• Proficiency in safety analysis tools (e.g., Medini Analyze, Ansys, Fault Tree+, FMEA software).
• Familiarity with autonomous vehicle architectures, including perception, planning, and control systems.
• Experience working with real-time embedded systems and software safety.
• Strong problem-solving, analytical, and communication skills.
• Experience with machine learning safety challenges in AVs.
• Knowledge of cybersecurity principles related to vehicle safety (ISO/SAE 21434).
• Experience in safety assurance for AI-driven systems.
• Previous work with automotive OEMs, Tier 1 suppliers, or AV startups

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Working Environment:

The work environment characteristics described here are representative of those a team member encounters while performing the essential functions of this job.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. 

While performing the duties of this job, the team member is regularly exposed to the office environment, outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The noise level in the environment is low to moderate. When traveling, the team member will be exposed to airports, airplanes, hotels and public transportation environments.

This role is based in our Pittsburgh or Las Vegas office and requires in-office days each week.

Mission Summary:

The Staff Systems Safety Engineer:

• Oversees the development and implementation of engineering safety processes for our autonomous vehicle systems
• Is responsible for reviewing hazards, risk assessments, and ensuring compliance with industry safety standards (ISO 26262, SOTIF, and ASIL).
• Collaborates with cross-functional teams, including software, hardware, and AI engineers, to ensure integration of safety into the design and validation of our AV system
  
  

Essential Duties:

• Ensure and oversee the development and implementation of  system safety processes for autonomous vehicle platforms.
• Ensure hazard analysis and risk assessments (HARA) for AV components and subsystems are conducted.
• Assist in the definition and verification of functional safety requirements in compliance with ISO 26262 and SOTIF (ISO 21448).
• Collaborate with hardware, software, and AI teams to integrate safety measures into perception, decision-making, and control systems.
• Support the development of failure mode and effects analysis (FMEA) and fault tree analysis (FTA) for AV systems.
• Ensure compliance with regulatory and industry safety standards, including SAE J3016, NHTSA, and UNECE WP.29.
• Ensure the development and execution of safety verification and validation plans, including simulation, testing, and real-world driving scenarios.
• Work with certification bodies and regulators to ensure safety case documentation and approval processes.
• Contribute to the development of safety culture within the organization by providing guidance and training
  
  

Qualifications:

Educational Requirements

• Bachelor’s or Master’s degree in Systems Engineering, Electrical Engineering, Computer Science, Mechanical Engineering, or a related field 

Technical / Specialized Knowledge, Skills, Abilities:

• 5+ years industry and 3+ years of experience in safety engineering for automotive, aerospace, or robotics systems.
• Strong knowledge of functional safety standards (ISO 26262, SOTIF, ASIL).
• Knowledge of systems / software engineering standards (INCOSE, ISO15288, ASPICE CMMI)
• Experience with hazard analysis, risk assessment, and safety case development.
• Proficiency in safety analysis tools (e.g., Medini Analyze, Ansys, Fault Tree+, FMEA software).
• Familiarity with autonomous vehicle architectures, including perception, planning, and control systems.
• Experience working with real-time embedded systems and software safety.
• Strong problem-solving, analytical, and communication skills.
• Experience with machine learning safety challenges in AVs.
• Knowledge of cybersecurity principles related to vehicle safety (ISO/SAE 21434).
• Experience in safety assurance for AI-driven systems.
• Previous work with automotive OEMs, Tier 1 suppliers, or AV startups

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Working Environment:

The work environment characteristics described here are representative of those a team member encounters while performing the essential functions of this job.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. 

While performing the duties of this job, the team member is regularly exposed to the office environment, outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The noise level in the environment is low to moderate. When traveling, the team member will be exposed to airports, airplanes, hotels and public transportation environments.

This role is based in our Pittsburgh or Las Vegas office and requires in-office days each week.

Motional’s Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

This role is based in our Pittsburgh office and requires 5 in-office days each week.

Mission Summary:

As a Senior PLM/PDM Engineer, you will ensure Motional’s PLM/PDM systems and engineering toolchains operate smoothly and reliably. You will be the go-to expert for resolving and escalating issues related to CAD tools, data management, and PLM–ERP connectivity. You’ll work cross-functionally with engineering, design, operations, and supplier teams to support day-to-day development activities while driving continuous improvement in processes and documentation.

What you’ll do:

• Ensure CAD tools, PLM/PDM systems, and engineering applications function properly; investigate, resolve, or escalate issues as needed.
• Develop and maintain documentation standards for the Hardware Engineering organization.
• Create and update CAD parts, assemblies, and libraries—including vehicle assemblies and vendor-provided models.
• Generate detailed 2D drawings (detail, section, assembly) following drafting standards and GD&T best practices.
• Support product development, sustainment initiatives, and internal department projects.
• Collaborate with designers, engineers, and technicians to ensure engineering documents and drawings are complete, accurate, and consistent.
• Perform drawing checks and manage engineering change orders (ECO/CO), including BOM updates and routing.
• Manage file structures, metadata, references, and overall CAD data organization.
• Troubleshoot and resolve CAD-related issues across the organization.
• Create, maintain, and manage Bills of Materials (BOMs).
• Maintain and organize the CAD library to support scalable design workflows.
• Work closely with internal and external fabrication teams to support design release, scheduling, and installation on vehicles or hardware systems.
  
  

What We’re Looking For:

• Strong understanding of mechanical drawings and electrical schematics.
• Experience with CAD data management systems; CATIA V5 and SolidWorks strongly preferred.
• Minimum 3 years of hands-on experience with 3D CAD tools (preferably CATIA V5 or SolidWorks).
• Skilled in developing 2D layouts in CATIA or SolidWorks.
• Solid working knowledge of GD&T principles.
• Experience with PLM tools, ideally PTC Windchill.
• Deep understanding of automotive and consumer-electronics connection systems.
• Ownership mindset with the ability to drive the CAD documentation process end-to-end—from design and release through fabrication, installation, schedule coordination, and change management.
• Strong communication and collaboration skills, with the ability to work proactively across global, cross-functional teams.
• Excellent planning, organization, and attention to detail.
• Proficiency with Microsoft Word/Excel or Google Docs/Sheets.
• Experience with Jira, QuickBase, NetSuite, or Zip is a plus.
• Strong work ethic and ability to support production schedules and team priorities.
• Ability to multitask across multiple projects and timelines.
• Bachelor’s degree in Mechanical Engineering or equivalent industry experience with a proven ability to apply engineering principles in real-world applications.

Mission Summary:

Our Component Engineering Team in Pittsburgh is seeking a Senior Hardware Engineer for Radar Components to lead the development of next-generation radar technology powering advanced mobility systems. In this role, you’ll take ownership of radar component design from concept to production, defining requirements, selecting and managing suppliers, integrating systems, driving testing and validation, resolving issues, and ensuring production readiness. 

This is an onsite, hybrid position based in Pittsburgh, PA.

What you'll be doing:

• Lead technical supplier management, coordinating technical activities and project milestones across internal and external stakeholders.
• Compile, define, and maintain complete sets of requirements for radar components.
• Collaborate cross-functionally with Perception, Systems, Mechanical, Vehicle, Manufacturing, Quality, Software, Cybersecurity, Diagnostics, and Reliability teams.
• Develop and support testing for ML-based algorithms, including test design, planning, execution, and data collection.
• Lead radar acceptance, performance, and characterization testing to ensure robust system performance.
• Support and drive vehicle integration efforts for radar systems.
• Conduct root cause analysis and oversee issue resolution to maintain quality and reliability.
• Lead continuous improvement projects focused on radar components and processes.

What we're looking for:

• Deep understanding of radar hardware, radar DSP, and radar testing and performance.
• Proven experience developing automotive radar components and radar system design.
• 5+ years of experience in the automotive or a related industry.
• Experience with multi-domain controllers, secure gateways, or ADAS controller development.
• Comfortable debugging, disassembling, modifying, and installing electrical and mechanical systems in vehicles.
• Strong ability to operate within rigid design, integration, and time constraints.
• Basic knowledge of vehicle electrical and networking systems (CAN, LIN, Ethernet, etc.).
• Strong communication skills with the ability to collaborate globally across teams and levels to drive project success.
• Self-motivated, organized, and flexible individual with the ability to balance and prioritize multiple diverse projects.
• Creative and resourceful problem-solver who ensures quality results independently and in teams.
• Hands-on vehicle integration experience, including wiring harnesses and packaging, is preferred.
• Bachelor’s degree in Engineering (STEM) or a related field.

This position may require the use of power tools, as defined by OSHA (electric, pneumatic, liquid fuel, hydraulic, or powder-actuated tools). While performing job duties, employees may be required to convey and detect communication, remain stationary for up to 50% of the time, move within designated areas, and operate office equipment. The role may occasionally involve moving objects up to 50 pounds.

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 Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

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.

Mission Summary:

As a seasoned expert in Perception Capabilities, you'll field cutting-edge software products and solutions using state-of-the-art computer vision and deep learning. Your breadth of experience spans critical problem areas like detection, classification, segmentation, and tracking, along with essential supporting functions such as data engines, labeling policies, training pipelines, model optimization, simulation, and testing. You're driven by seeing your work significantly impact the product, taking initiative and owning outcomes.

You're eager to apply these skills to the perception stack of self-driving vehicles. You understand the unique challenges of safety-critical, open-world applications and are committed to ensuring engineering excellence and rigorous evaluation.

You'll devise creative solutions to complex problems, collaborating with interdisciplinary, capability-focused teams across the organization to design, implement, and validate end-to-end solutions.

What you’ll be doing:

• Lead the development and implementation of solutions that span across perception components and directly interface with downstream modules in the autonomy system.
• Analyze the performance of the perception subsystem to proactively identify potential limitations with respect to a set of system-level capabilities. Document potential hazards and lead the cross-team efforts to eliminate or mitigate them.
• Collaborate on innovative solutions to address “long tail” challenges. For example, developing techniques for synthetic data generation, advanced data mining, or leveraging language embeddings in our onboard models.
• Depending on your background and interests, you may also help optimize and deploy models to the vehicle, ensuring they operate within the constraints of our onboard hardware and meet our functional requirements and interface specifications.
• Interface with systems and safety engineers, test engineers, and data analysts to ensure appropriate requirements, test coverage, and performance metrics

What We’re Looking for:

• Master's or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field; or equivalent industry experience
• Strong leadership skills in executing large, complex technical initiatives
• Track record of successful interdisciplinary work and product-focused engineering
• Broad understanding of Deep Learning algorithms, architectures, and applications
• Experience designing, training, and analyzing neural networks for applications relevant to perception
• Fluency in Python, including common libraries for deep learning (PyTorch), scientific computing, and data analysis and visualization
• Advanced knowledge of software engineering principles, including software design, source control management, build processes, code reviews, and  testing methods 
• Excellent communication and interpersonal skills
• Experience mentoring and leading others

Bonus Points:

• Experience shipping a “real” product and balancing ongoing support with next-generation innovation
• Experience developing safety-critical products or components
• Publications in relevant conferences (CVPR, ICML, NeurIPS, etc.)
• Strong programming skills in C++ and/or CUDA programming
• Experience with TensorRT and model quantization

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 Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

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.

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 Senior Machine Learning Engineer on the Data Mining team, your mission is to build the "Brain" of this engine: designing massive multimodal Teacher models that understand the world, and distilling them into hyper-efficient Student models that can scour exabytes of data in near real-time. You will work at the intersection of large-scale representation learning, retrieval optimization, and reasoning systems. Your work will directly influence how we compress knowledge into efficient encoders for fast search, and how we apply reinforcement learning to optimize data discovery workflows and intelligent querying. By building smarter mining tools, you will accelerate the entire model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Architect and Train Distilled Models: Design and implement teacher-student model frameworks for multimodal sensor data. Develop training pipelines for knowledge distillation. Ensure student models maintain high accuracy while drastically reducing inference latency and memory footprint.
• Reinforcement Learning for Data Discover: Build RL-based policy learning and reasoning systems for autonomous driving applications. Implement and scale RL training workflows (e.g., PPO, DQN, actor-critic methods) for simulation and real-world interaction. Explore reward shaping, environment modeling, and multi-agent RL where applicable.
• Optimize Model Deployment for Real-Time Inference: Collaborate with backend engineers to deploy distilled and RL models into production. Optimize for latency, throughput, and hardware efficiency across GPU/CPU clusters. Implement model versioning, A/B testing, and monitoring for performance regressions.
• Research and Integrate Agentic Systems: Explore and prototype agentic workflows for autonomous reasoning, chain-of-thought prompting, and goal-directed behavior. Integrate such systems into our broader autonomy stack as experimental or production components.
• Drive Production Reliability: Establish patterns for graceful degradation, fault tolerance, and cost optimization. Operate Omnitag as a mission-critical data platform serving the entire ML organization, with a focus on reliability, debuggability, and operational excellence.
• Mentor and Collaborate: Work closely with ML scientists, data engineers, and autonomy teams to translate research advances into scalable engineering solutions. Guide junior engineers in best practices for model training, evaluation, and deployment.

What We're Looking For:

• BS in Computer Science, Machine Learning, or related field, or equivalent professional experience.
• 6+ years of hands-on experience in machine learning engineering, with a focus on model post training, optimization, and deployment.
• Strong experience with model distillation or teacher-student training - practical knowledge of loss functions, training strategies, and evaluation of compressed models.
• Proven experience with reinforcement learning in production or research settings: policy optimization, reward design, simulation environments, and RL-based reasoning.
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX).
• Strong software engineering fundamentals: testing, CI/CD, containerization, and system design.
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for inference.
• Demonstrated ability to ship production-grade ML systems and mentor team members.
• Demonstrated track record of shipping robust, well-tested, production-grade systems and mentoring junior engineers

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or related field.
• Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
• Background in autonomous driving, robotics, or real-time decision-making systems.
• Familiarity with multimodal learning, sensor fusion, or embodied AI.
• Experience building active learning loops, using the model to find the data that breaks the model.
• Experience with ML-based data mining, active learning, or contrastive learning.
• Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
• Publications or open-source contributions in RL, distillation, or efficient ML.
  
  

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.

You’re an engineer who is excited to work on cutting-edge software products and solutions using state-of-the-art computer vision and deep learning. You have a solid foundation in areas like detection, classification, segmentation, or tracking—whether through previous roles, internships, or research—and you’re eager to apply those skills in an impactful, production-focused environment.

You’re curious, motivated, and ready to learn from experienced teammates. You enjoy solving challenging technical problems, asking thoughtful questions, and collaborating with others to build high-quality software.

You’re excited about contributing to the perception stack for self-driving vehicles and learning what it means to build technology for safety-critical, open-world applications.

What you’ll be doing:

• Contribute to the design, development, and improvement of perception components that support downstream modules within the autonomy system.
• Help analyze perception system performance to identify areas for improvement and participate in efforts to address them.
• Work with teammates to explore creative approaches to “long-tail” challenges—for example, experimenting with synthetic data, data mining techniques, or new model architectures.
• Depending on your background and interests, you may also help optimize and deploy models to the vehicle, ensuring they operate within the constraints of our onboard hardware and meet our functional requirements and interface specifications.
• Interface with systems and safety engineers, test engineers, and data analysts to ensure appropriate requirements, test coverage, and performance metrics

What We’re Looking for:

• Master's or Ph.D. in Machine Learning, Computer Science, Robotics, or a related field; or equivalent industry experience
• Solid understanding of fundamental deep learning concepts and computer vision techniques
• Experience building, training, or evaluating neural networks
• Proficiency in Python and familiarity with libraries like PyTorch or similar
• Exposure to software engineering fundamentals—version control, code reviews, testing, and collaborative development
• Clear communication skills and willingness to ask questions, share ideas, and work with others

Bonus Points:

• Previous experience with sensor fusion and/or previous exposure to the AV industry
• Experience shipping a “real” product and balancing ongoing support with next-generation innovation
• Exposure to safety-critical products or components
• Publications in relevant conferences (CVPR, ICML, NeurIPS, etc.)
• Strong programming skills in C++ and/or CUDA programming
• Experience with TensorRT and model quantization

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems, and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

We are seeking an experienced and visionary Principle Level Tech Lead Manager to build and lead our new Machine Learning (ML) Acceleration team. This pivotal role will drive the strategy, development, and execution of initiatives aimed at significantly accelerating ML model training. The ultimate goal is to drastically reduce the development cycle for new ML models and enable rapid hot-patching for issues within our deployed autonomous vehicle services.

You will be a hands-on leader, blending deep technical expertise in ML systems and performance optimization with strong leadership and people management skills. You will recruit, mentor, and grow a high-performing team of engineers, fostering a culture of innovation, collaboration, and continuous improvement.

What you'll be doing:

• Team Leadership & Management:
• Build, lead, and manage a high-performing team of ML and infra engineers focused on acceleration.
• Provide technical guidance, mentorship, and career development opportunities to team members.
• Foster a collaborative and inclusive team environment.
• Define team goals, priorities, and roadmap in alignment with company objectives.
  
  
• Technical Strategy & Execution:
• Define the technical vision and strategy for ML acceleration across the organization.
• Identify and evaluate cutting-edge technologies and methodologies for speeding up ML training, including but not limited to data pipeline optimization, large scale distributed training, data loader optimization, hardware acceleration, and model optimization techniques.
• Design, develop, and implement scalable and efficient ML acceleration solutions.
  
  
• Cross-functional Collaboration:
• Collaborate closely with ML research, ML Training platform, and product teams to understand their needs and integrate acceleration solutions seamlessly.
• Communicate complex technical concepts and strategies to both technical and non-technical stakeholders.
• Act as a technical expert and advocate for ML acceleration initiatives across the company.
  
  
• Impact & Measurement:
• Regularly measure and report on the impact of acceleration efforts.
• Continuously seek opportunities for further optimization and innovation.
  
  

What we're looking for:

• Experience:
• Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience
• 8+ years of experience in software engineering, with at least 5+ years focused on Machine Learning systems and model performance optimization.
• 3+ years of experience in a technical lead or management role, with a proven track record of building and leading high-performing teams.
• Extensive experience with large-scale ML model training and deployment, ideally in a production environment.
• Strong understanding of distributed systems and cloud computing platforms (e.g., AWS, GCP, Azure).
  
  
• Technical Skills:
• Deep expertise in ML frameworks such as PyTorch or JAX.
• Proficiency in performance profiling and optimization techniques for Deep Neural Networks.
• Strong programming skills in Python; C++ experience is a plus.
• Knowledge of MLOps principles and practices.
  
  
• Leadership Skills:
• Exceptional leadership, communication, and interpersonal skills.
• Ability to attract, hire, and retain top engineering talent.
• Proven ability to drive complex technical projects from conception to completion.
• Strong problem-solving skills and a proactive, results-oriented mindset.
• Ability to thrive in a fast-paced, dynamic environment.

Mission Summary:

The Autonomous Vehicle (AV) Test Engineering team at Motional is responsible for validating the safety, functionality, and performance of our self-driving technology through rigorous, system-level testing. As a Senior AV Test Engineer, you will take a lead role in the strategy, planning, and execution of comprehensive test campaigns that span perception, planning, and control systems across virtual, closed-course, and public road environments.

In this role, you will guide test development efforts across multiple AV subsystems, mentor junior engineers, and drive improvements to our tooling, test infrastructure, and methodologies. You will lead cross-functional initiatives that directly impact release readiness and safety assurance, translating high-level engineering requirements into scalable test plans and measurable quality outcomes. Your work will contribute to iterative development, fault injection analysis, and validation of safety-critical systems that meet the highest standards for reliability and compliance.

Essential Duties:

Technical Leadership & Validation:

• Lead the planning, design, and execution of validation campaigns across simulation, SIL, HIL, and on-vehicle environments, with a focus on perception, planning, and control systems.
• Serve as the technical lead for scenario-based testing, utilizing platforms like Applied Intuition or equivalents for synthetic and re-simulation use cases.
• Lead AV capability campaigns, employing AB Dynamics equipment for system-level validation and performance benchmarking.
• Own the creation and execution of test plans for complex mechatronic and software systems, including drive-by-wire (DBW), braking, steering, and system integrations.

Test Infrastructure & Analysis:

• Develop and maintain robust test infrastructure using Python, Shell, and automation frameworks, ensuring modular, reusable, and scalable test architecture.
• Conduct detailed analysis of logs and system behavior, supporting root-cause investigations across AV software and hardware components.
  
  

Quality Assurance & Compliance:

• Participate in and lead QA review cycles, helping to define entry/exit criteria, regression coverage, and release readiness gates.
• Ensure traceability and compliance by documenting procedures, results, and outcomes using Jira, GitLab, and Confluence.
• Contribute to compliance with safety-critical standards such as ISO26262, ISO21448 (SOTIF), and ISO9001.
  
  

Collaboration & Mentorship:

• Represent the Test Engineering function in cross-functional planning meetings, collaborating closely with perception, planning, controls, and safety teams.
• Mentor and support junior Test Engineers, providing technical guidance and fostering a culture of continuous learning and improvement.
  
  

Strategic Adaptation & Support:

• Continuously adapt and optimize test strategies in response to evolving product requirements, architectural shifts, and real-world findings.
• Support after-hours testing or incident triage as needed by fleet or field operations.
• Travel domestically on occasion to support on-site testing or operational deployments.
• Perform additional duties as assigned.

Required Qualifications:

• Bachelor's degree or higher in Engineering, Robotics, ECE, Computer Science, or a related technical field.
• 5+ years of experience in software QA or system testing, including AV, ADAS, robotics, or safety-critical systems.
• Demonstrated expertise in test strategy, test case development, test execution, and automation for complex mechatronic or autonomous systems.
• Experience leading end-to-end testing across software stacks and physical systems, including SIL, HIL, and real-world deployments.
• Strong analytical skills with proficiency in debugging, log parsing, and root cause analysis.
• Excellent verbal and written communication skills, with the ability to drive cross-functional alignment and effectively report technical findings.
• Proven ability to lead technical efforts, mentor junior engineers, and operate with minimal oversight.
• High level of initiative, ownership, and accountability in a fast-paced, startup-style engineering environment.
• Flexible schedule and willingness to support late meetings, night shifts, or urgent test activities as required.

Preferred:

• Master’s degree in a relevant field.
• Deep familiarity with CAN-based tools (CANalyzer, CANoe) for fault injection, bus analysis, and subsystem verification.
• Working knowledge of industry standards for safety-critical systems such as ISO26262, ISO21448 (SOTIF), and ISO9001.
• Familiarity with AV safety case development or safety validation workflows.
• Experience with robotic middleware (e.g., ROS), cloud telemetry systems, or AV data pipelines.
• Experience in a cross-site or global engineering organization.
  
  

Physical Demands:

While performing the duties of this job, the employee is frequently required to sit, talk, or hear. The employee is occasionally required to stand and at times for long periods; walk; use hands to finger, handle, or feel; reach with hands and arms. The employee must occasionally lift and move up to 50 pounds.

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job.  Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions.

While performing the duties of this job, the team member is regularly exposed to outside weather conditions, road conditions, and pedestrian traffic.  The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and airborne particles.  The noise level in the environment is low to moderate.

Motional AD LLC is an Equal Employment Opportunity employer, and we welcome all qualified applicants.  All applicants will receive impartial consideration regarding race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation, or another legally protected status.  Motional AD LLC is a Drug-free workplace.

Mission Summary

You will be responsible for power and signal distribution design for Autonomous Vehicles. We are looking for someone who is proficient in hardware design life cycle, comfortable working in a high paced environment, and someone who can adapt quickly.  You will work cross functionally to gather details required for proper connections, generate system diagrams, electrical schematics, wiring harness diagrams, and assist with assembly and build documentation. You will also create detailed component and system qualification, validation test plans, and perform & oversee testing. 

We are looking for a detail-oriented problem-solver, able to employ critical thinking and time management skills and can work effectively both independently and in teams. Work with people of diverse backgrounds and develop creative and innovative ways to improve processes.

The Motional Pittsburgh office is located in the new Hazelwood Green development, a culmination of the city’s goal of restoring an economic driver to the neighborhood in a thoughtful, inclusive, and sustainable way. With views along the Monongahela river, the Pittsburgh office is in the heart of this new state of the art development.

What you'll be doing:

• Quickly gain a deep understanding of system architecture and specifications to implement the detailed electrical design of the AV system into a vehicle platform.
• Work within an interdisciplinary team to troubleshoot, test, and fix electrical and system issues in prototype vehicles and test fixtures.
• Support product design reviews.
• Review internal and external requirements and specification documentation.
• Perform worst case analysis and simulation to ensure compliance to system requirements.
• Generate system diagrams, electrical schematics, wiring harness diagrams, and assist with assembly and build documentation.
• Create detailed component and system qualification and validation test plans and perform / oversee testing.
• Support EMC certification testing and develop and maintain electrical DFMEA.
• Utilize structured problem-solving techniques for test failure resolution.

What we're looking for:

• 6+ years of experience in electrical engineering.
• Ability to read and interpret schematics and assembly drawings.
• Lab equipment experience with power supplies, oscilloscopes function generators and multimeters.
• Familiarity with wire harness design process and software tools to help EE team design vehicle power and signal distribution
• Ability to multitask across various project activities and work with a global team.
• Ability to provide hands-on debugging as needed during testing and evaluation.
• Experience with other vehicle communication networks (CAN, CAN-FD, Automotive Ethernet, LIN).
• Strong troubleshooting and debugging skills.
• Bachelor’s degree or higher in Electrical Engineering

Motional’s global headquarters are located at 100 Northern Avenue in Boston, MA. Nestled in the bustling Seaport district with sweeping views of Boston Harbor and downtown Boston, the office is located close to major transit lines and a quick walk to various restaurants and popular attractions.

Mission Summary:

Motional’s CORE team is responsible for our vehicle’s Compute and Onboard Runtime Environment. We are creating a world leading AI compute platform for autonomous vehicles. This is the system that executes the software and neural networks that make our vehicles autonomous. 

The Next-Gen Technologies team is part of CORE. We work at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s on-board vehicle architecture. If you are a software engineer and love the idea of working on embedded AI hardware and software systems to create the next generation of autonomous vehicles, we would love to talk with you. 

What You’ll Be Doing:

As a senior engineer in the Next-Gen Technologies team, you will help us improve the compute performance of our current generation and next-generation autonomous driving systems through participating in full lifecycle development from idea to proofs-of-concept to production. 

Specifically, you will:

• Focus deeply on ML model deployment, integration of multiple ML models, and ML model optimization on embedded compute platforms.
• Dive deep into the full ML software stack. Analyze ML workload performance on a variety of hardware processors, optimize ML models, improve ML software, and help us continually improve our stack through the application of efficient and effective ML approaches. 
• Design, develop, test, integrate, and optimize software and tools on a variety of ML compute architectures.
• Collaborate with deep learning experts in perception, prediction, and other autonomous driving application areas to enable algorithms on GPU, NPU, and other ML accelerator architectures.
• Optimize the utilization of GPU/NPU resources and sharing of GPU/NPU access across multiple programs running on the same system.
• Lead designs to determine the needs of the system and how to best meet those needs through continually improving our ML software stack.
• Advise peers and management on technical matters.

What We’re Looking For:

• Experience with machine learning accelerators, including GPUs, NPUs, TPUs, and their programming environments, including CUDA, TensorRT, or similar technologies.
• Strong experience with modern C++ development in a Linux environment.
• Experience with parallel and high-performance computing.
• Comfortable with experimentation and evaluating different options as we work towards finding solutions that work. 
• A degree in Software Engineering, Computer Science, Electrical or Electronic Engineering, or similar technical field of study, or you have equivalent knowledge gained through your practical experience.

Preferred, but not required:

• Experience with PyTorch, TensorFlow, ONNX, and/or other ML frameworks. 
• Experience with embedded systems development for ARM-based system-on-chip architectures.
• Experience working in a MLOps or DevOps environment.
• Passion for self-driving technology and its potential for positive impact on the world.
  
  

This role is hybrid from our Boston office. It requires two in-office days each week, ideally Tuesday and Thursday.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Autonomy Analytics team is responsible for evaluating the performance of our autonomous software using data, statistics, and machine learning. Combining data from real-world testing with our extensive simulations, our team builds the metrics and analytics that ensure our product is safe, reliable, and delights our customers. 

Our team is spread geographically with some members on-site in Pittsburgh, Palo Alto, and Dearborn. Others work fully remotely.

What you’ll do: 

• Translate loosely defined questions into clear requirements, metric definitions, and analytical deliverables
• Partner closely with software development teams, test engineering, product, and analytics partners to understand needs and deliver trusted data products
• Build and maintain scalable data models in Google BigQuery and similar cloud data platforms to support reporting, analysis, and operational decision-making
• Develop dashboards and lightweight data applications in Apache Superset, Plotly Dash, or similar tools for technical and business stakeholders
• Investigate source data, identify quality issues, and implement durable fixes that improve accuracy, consistency, and reliability
• Create reusable datasets, testing practices, and documentation that strengthen trust in data and improve self-service access
• Balance near-term dashboard development with long-term data modeling work to support both speed and scale
• Communicate findings, assumptions, and tradeoffs clearly to internal stakeholders and external platform or data partners as needed

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Experience building and maintaining analytics-ready data models in Google BigQuery or a similar cloud data warehouse
• Experience using dbt or a similar data transformation framework to develop tested, documented, and maintainable data pipelines
• Experience designing dashboards and analytical applications in Apache Superset, Tableau, or similar reporting and visualization tools
• Strong SQL skills, including complex transformations, data validation, and query optimization
• Experience with Python for data analysis and application development, including the ability to contribute to and maintain Plotly Dash dashboards
• Demonstrated ability to succeed in ambiguous environments by defining requirements, shaping metrics, and creating structure from incomplete problem statements
• Experience partnering with software development, test engineering, product, or similar cross-functional teams to deliver measurable outcomes
• Strong foundation in data modeling, dashboard design, documentation, and quality assurance practices
• Strong written and verbal communication skills with the ability to explain analytical concepts and findings to varied audiences

Nice to have: 

• Experience supporting autonomous vehicle development or other complex hardware and software products
• Experience working with telemetry, operational, or product usage data at scale
• Experience building shared metrics and self-service reporting solutions for engineering and product organizations
• Experience with front-end technologies such as HTML, CSS, JavaScript, or React to support customization and enhancement of data applications and dashboards

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

About The Role

The AI innovation team at Agility works on building and deploying next-generation robot foundation models and end-to-end policies on humanoid robots. Your goal will be to develop and test cutting-edge methods for imitation learning and reinforcement learning on humanoid robots, in order to establish the techniques necessary for humanoid robots to perform different real-world tasks. You will work on a team, running experiments on humanoid robots, and will research and implement methods which can be transferred into production.

About the Work

• Design, train, and deploy robust policies for locomotion, manipulation, and dynamic interactions with the environment.
• Develop core reinforcement learning infrastructure, including scalable training pipelines and evaluation frameworks.
• Design and implement new simulation environments and tasks to support training and deployment of control policies.
• Develop, design, and test imitation learning methods
• Collaborate with Robotics Software and AI engineering teams to develop policies which can be transferred to production

About You

• 3+ years of experience developing and deploying learning-from-demonstration
• Strong programming skills in Python, with proficiency in deep learning frameworks such as PyTorch.
• Experience with modern learning-from-demonstration tools like DiffusionPolicy
• Experience with robot data collection, training, and testing on hardware to perform manipulation tasks.
• Ability to work collaboratively in a fast-paced environment to deliver safe, high-quality software
• MS in Robotics, Computer Science, or a related field.

Bonus Points

• PhD in Robotics, Computer Science, or a related field.
• Publications in top ML or robotics conferences (e.g. NeurIPS, ICML, CoRL, RSS, ICRA).
• Familiarity with robot simulation environments (e.g. Mujoco, Isaac Sim) and sim-to-real transfer techniques.
• Experience with modern reinforcement learning techniques for locomotion, manipulation, and whole-body control
• Experience with writing performant, high quality software in C++

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Embedded Software team develops foundational platform software that is critical to development across the company. The team develops FreeRTOS, SafeRTOS, and bare metal environments for both QM and ASIL applications on a variety of embedded targets including ARM. Projects often impact all levels of the stack from the bootchain to applications and usually require cross-functional collaboration with other engineering teams. We have a strong passion for technical excellence and rigorous compliance with ASPICE and ISO26262. 

What you’ll do: 

• Own development of end-to-end embedded software features from concept through delivery.
• Deliver embedded software that runs on multiple platforms.
• Create architectures and development plans and help the team execute on them effectively.
• Collaborate with other Latitude and Ford software teams to ensure related dependencies are identified and resolved.
• Implement device drivers and bring-up new hardware for the first time.
• Mentor junior engineers and help set the direction of the program through deep technical analysis. 
• Establish and refine best practices for safety-critical embedded software development.

What you'll need to succeed:

• Passion for Embedded Software Development in C and C++
• Experience with one or more of the following:
• FreeRTOS and SafeRTOS development on ARM architectures
• ISO26262, SOTIF, & ASPICE or similar standards for safety critical applications
• Development and deployment of security features such as secure boot, secure communication, secure key management
• Embedded development on multi-core, ARM-based SOCs
• Strong project leadership and communication skills to collaborate across the ASPICE V-model
• Flexibility to work across all layers of the software stack from device drivers to applications
• Expertise in debugging low-level performance issues across a complex embedded system
• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and 2+ years of relevant experience)

Nice to have (optional):

• Experience using the gtest framework for unit test development
• Development and support of software tools and infrastructure that improve developer experience
• Expertise in Linux-based software development and related technologies including gtests, Python, Bazel, and Docker.
• Development with Automotive Ethernet, UDS, DOIP, Some/IP

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $218,240 - $327,360 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

We are seeking a highly skilled Senior Software Engineer specializing in Time Synchronization and Embedded Networking for autonomous systems. You will be responsible for the hands-on design, development, and technical problem-solving for critical timing and networking solutions. This role requires deep expertise in precision timing protocols and functional safety standards to ensure the robust, reliable, and safe operation of our next-generation autonomous platforms.

What you’ll do: 

• Lead the design, development, and implementation of high-precision time synchronization solutions for autonomous systems, utilizing IEEE 1588 (PTP) and IEEE 802.1AS (gPTP), including architecting clock distribution, leveraging hardware timestamping, and implementing efficient time distribution mechanisms
• Design and execute comprehensive testing, validation, and performance optimization strategies for timing systems, ensuring sub-microsecond accuracy, and diagnose and resolve complex timing, latency, and synchronization issues (e.g., task starvation, offset deviations)
• Design, develop, and validate safety-critical time synchronization and networking components in compliance with functional safety standards (e.g., ISO 26262), including creating safety monitors, contributing to safety analyses (HARA, FMEA), and developing verification plans
• Design, develop, and optimize embedded networking solutions, including configuring Ethernet switches and their forwarding mechanisms (e.g., Address Lookup Engines), managing multicast, unicast, VLANs, static ARP/MAC entries, and debugging network traffic flows
• Actively contribute to technical and architectural discussions, collaborate with cross-functional teams and external partners, and contribute to technical documentation and industry standards related to timing and networking

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• 5+ years of experience in embedded systems software development, with a significant focus on time synchronization
• Expert-level knowledge and hands-on experience with IEEE 1588 (PTP) and IEEE 802.1AS (gPTP) in real-world embedded systems
• Strong understanding of time synchronization architectures, measurement methodologies, and standards (e.g., NTP, GNSS-based synchronization)
• Proven hands-on experience with timing measurement instrumentation and analysis tools
• Strong understanding and practical experience with functional safety standards (e.g., ISO 26262) for software and systems
• Proficiency in C and modern C++ programming for embedded systems, particularly in RTOS or embedded Linux environments
• Proven experience in designing, implementing, and analyzing network protocols and embedded Ethernet switches
• Excellent problem-solving, analytical, and debugging skills for both time synchronization and networking
• Strong communication skills, with the ability to articulate complex technical concepts and collaborate effectively

Nice to have: 

• Experience with other automotive or industrial communication protocols (e.g., CAN, Automotive Ethernet)
• Knowledge of broader Time-Sensitive Networking (TSN) standards beyond PTP/gPTP
• Experience with simulation tools
• Scripting proficiency (e.g., Python) for automation, testing, and data analysis
• Experience with hardware-in-the-loop (HIL) or software-in-the-loop (SIL) testing
• Familiarity with various System-on-Chips (SoCs) and their networking peripherals
• Knowledge of network security concepts like MACSec in embedded systems
• Experience with kernel-level programming, device drivers, and/or real-time systems software

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

Latitude Cloud Platform engineers create reusable architecture via infrastructure as code for Latitude teams to leverage as common shared components and educate Latitude teams on how to architect their solutions for scale, security, and reviewed changes through automation. This includes ownership of the workload ecosystem on Kubernetes running on public and hybrid cloud environments.

The Cloud Platform team interacts with engineering teams including ingest/data processing, mapping, labeling, triage, machine learning (detection, prediction, tracking), motion planning/control, offline simulation, and release/deployment teams to unify development practices and scalable efficiency of cloud/cloud native technologies.

What you’ll do: 

• Architect and scale a multi-tenant, hybrid-cloud Kubernetes platform to ensure seamless workload portability across public and internal environments
• Develop custom Kubernetes operators and self-service abstractions to simplify complex infrastructure management for autonomous vehicle engineering teams
• Optimize high-performance distributed workloads by architecting specialized compute environments for ML and simulation on heterogeneous hardware
• Standardize end-to-end GitOps workflows and CI/CD pipelines to automate security, networking, and observability across the infrastructure lifecycle
• Provide technical leadership and architectural guidance to ensure engineering teams build resilient, cost-effective services aligned with cloud-native best practices
• Manage the lifecycle of critical platform components like service mesh and networking while proactively resolving systemic bottlenecks in hybrid cloud environments

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Hands on development in Python, Go, or Java to create production level services that incorporate CI/CD
• Experience in using infrastructure as code to automate the creation of cloud resources. E.g. Terraform, CloudFormation, or others
• Strong experience with architecting/deploying scalable services and workloads in the cloud (AWS, GCP) and/or cloud native environments
• Strong experience with deployment management/scheduling/high availability/failure modes for distributed applications and compute workloads running on CPUs and GPUs
• Understand engineering design limitations and provide guidance for teams to scale their deployments in the cloud so that they can achieve desired performance within budget
• Experience creating reusable deployment patterns for teams to adopt, that incorporate networking, security, monitoring, logging, alerting, continuous integration and deployments
• Understanding of API specification languages (e.g. Open API/gRPC) and the ability to create reusable code via code generation, templates, and other rapid development techniques for teams to consume
• Leverage and modify open source tools to meet unique requirements for internal teams, including but not limited to Kubernetes, Prometheus, FluentD, Istio, Envoy, CoreDNS, etcd, Flux, among others

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Onboard Platforms team is an embedded software team responsible for the development and maintenance of the operating system, on-vehicle network, timesync, vehicle interface, and security for the L1/L2/L3 autonomous vehicle compute clusters.  

What you’ll do: 

• Deliver safe and efficient embedded software for state-of-the-art sensing systems
• Produce high-quality, maintainable code using C++
• Design and optimize in-vehicle networks to communicate with the sensors and provide the common timebase for the autonomy software
• Design, implement, and test full-stack software running in resource-constrained environments
• Work closely with a multidisciplinary team of hardware, software and system engineers to ensure the success of our product

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong experience developing embedded applications and systems using C++
• Proficient in network communication concepts including protocols, physical layer requirements, bandwidth characteristics, and configuration
• Knowledge of TCP/IP, Ethernet, CAN, and experience working with Marvell/Broadcom (or similar automotive-grade) Ethernet switches, including low-level configuration, firmware interaction, and troubleshooting hardware-software interface issues
• Strong software design, algorithm, problem-solving, and analytical skills
• Strong test-first design mindset
• Experience with multi-processor SoCs or similar embedded processors
• Experience with time synchronization, IEEE802.1AS, and Linux PTP is preferred
• Prefer candidates with experience developing software for highly complex, safety-critical sensing systems with specific emphasis on network design for fault detection, and time synchronization for safety-critical data paths

Nice to have: 

• Strong modern C++ skills
• Understanding of networking and time-sensitve networking
• Experience developing Linux device drivers for Ethernet, GPU, PCIE or flash devices like UFS, eMMC, NVMe
• Experience with Yocto/OpenEmbedded, buildroot, or similar Linux packaging technologies
• Track record of technical leadership in automotive or related fields taking products to production

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Bench Infrastructure team is responsible for maintaining critical hardware test infrastructure services at Latitude. This infrastructure supports high-velocity code validation for hundreds of developers, on custom hardware for our next-generation automotive autonomy solution. We are seeking a talented Senior Software Engineer to join the team and ensure the test infrastructure is ready to support a significantly larger scale.

What you’ll do: 

• Design and implement software solutions to ensure the usability and supportability of hardware-in-the-loop test execution services
• Deliver streamlined tools which minimize friction for software engineers to build, test, and debug autonomy software
• Identify and resolve stability problems and security vulnerabilities across the entire stack, ensuring the platform remains resilient and secure as the hardware test infrastructure grows
• Leverage performance metrics to pinpoint and remove inefficiencies in test infrastructure logic and complex test runtimes
• Enhance the performance and reliability of test execution, ensuring scheduling logic balances both system throughput and urgent job prioritization
• Maintain performance analysis test logic, ensuring reliable execution and data-driven validation of software performance across diverse hardware configurations
• Act as a technical bridge between Autonomy Software Engineering, IT, and Operations to ensure cross-functional pain points are resolved with scalable technical solutions

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Strong communication, problem solving, task prioritization and teamwork skills 
• Proficiency with Python programming language, navigating a large codebase, and ability to learn other languages or technologies as needed
• Proven track record of designing, developing, and deploying full-stack applications at scale a Kubernetes-orchestrated production environment
• Ability to diagnose and resolve intricate problems in distributed systems and mitigate technical debt
• Experience with Linux systems, networking, distributed filesystems, and databases using SQL and ORMs

Nice to have: 

• Experience with full stack technologies: React, TypeScript, Flask, Postgres, & ORMs 
• Experience with DevOps technologies: AWS, Kubernetes, Docker, Terraform, & Ansible
• Experience with Data Warehousing and Visualization: BigQuery, & Superset
• Experience building validation tools for heterogeneous hardware environments, including Linux-based edge devices, robotics, or ML-driven applications
• Experience with C++ & Bazel

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.  

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Latitude AI Autonomy Behavior team is responsible for designing and building systems that allow an autonomous vehicle to understand the current scene around it, predict how the scene will evolve in the future and make decisions on how to respond.  The team focuses on deploying SOTA algorithms in limited compute environments, and writing efficient software architectures that take advantage of hardware optimizations.

You will play a key role in improving the quality and safety of the autonomy system through the optimization and integration of both modern (transformer, etc…) and classical ML (Random Forest, SVM, etc..) models. Our models utilize time series data to solve regression, generation, and classification tasks.  Improving model inference and latency on our target hardware allows us to deploy deeper and more powerful models and improve the vehicle’s ability to reason in complex situations.

What you’ll do: 

• Integrate and optimize algorithms and models for predicting the future behavior of other traffic participants in real time and planning a proper response
• Measure the statistical properties and quality of predictions and plans
• Build a system that safely handles nominal and out-of-distribution driving events
• Evaluate and verify the system's performance on real-world and simulated data
• Improve and deliver reliable software through continuous integration, automated testing and code reviews
• Collaborate across different teams to jointly achieve objectives in improving system performance
• Monitor system performance and ensure designs and implementation stay within resource constraints

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Fluency in modern C++ including good software design skills and experience with Python
• Familiarity with PyTorch, ONNX and deployment/optimization of models is desired
• Knowledgeable in areas pertaining to probabilistic inference, probability theory, statistics
• Application of Machine Learning in classification, regression, time series forecasting
• Willingness to dive into anything, but know when to ask for cross team collaboration
• Industry experience writing production-quality, performance-critical code, and maintaining large codebases is desired
• Strong written and verbal communication skills are required

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $179,200 - $268,800 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire. Visa sponsorship is available for this position.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

About Us

Are you ready to build the future of supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.

If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

You'll be embedded at the intersection of hardware and software, collaborating with Autonomy and MHE Vision engineers to bring cutting-edge systems to life. You'll partner with hardware designers on sensor validation, working closely with systems engineers on integrated testing, and have a direct line to QA leadership in shaping overall test strategy

About the Role

We are looking for a Hardware / Software QA Engineer to own testing at the boundary between our physical hardware and software systems. You will validate sensors, firmware, and software components that work correctly together end-to-end — closing a critical quality gap for both our Drone and MHE Vision platforms.

This is a rare hybrid QA role that spans embedded devices, sensor systems, and software stacks. You’ll work hands-on in our Pittsburgh lab with real hardware while contributing to the quality infrastructure that keeps production systems running reliably for our customers.

What You’ll Do

• Execute hardware-software integration tests in the Pittsburgh lab, validating sensor behavior, firmware functionality, and end-to-end data flow from physical devices through the software stack
• Design and document repeatable test procedures for sensor integration and firmware validation across both the Drone and MHE Vision platforms
• Identify and classify defects at the hardware-software boundary — distinguishing hardware faults, firmware bugs, driver issues, and application software errors — and route clearly to engineering owners
• Build and maintain hardware-software integration test suites, including firmware validation, sensor calibration tests, and embedded release regression testing
• Contribute to cross-platform test infrastructure that serves both product lines and establish defect classification and routing processes
• Collaborate with systems engineers on integrated system tests and with the ML team on validating how sensor data feeds into perception pipelines

What You’ll Need

• 3–5 years of QA or test engineering experience with genuine exposure to both hardware and software testing — not purely one side
• Hands-on experience testing sensors (cameras, LiDAR, IMUs, or similar), including calibration, data quality assessment, and performance characterization
• Embedded firmware validation experience: flash/update procedures, functional verification, regression testing, and failure mode analysis
• Python proficiency for test automation, data processing, log analysis, and building test utilities
• BS in Computer Science, Electrical Engineering, Computer Engineering, Mechatronics, or a related technical field; must be willing to work on-site in Pittsburgh

Nice to Have

• Experience with embedded platforms such as NVIDIA Jetson or ARM-based devices
• Familiarity with communication protocols (UART, SPI, I2C, USB) and basic lab instruments (oscilloscopes, logic analyzers)
• CI/CD experience for embedded or hardware-in-the-loop testing
• Exposure to computer vision or ML pipelines — understanding how sensor data feeds into inference systems

About Us

Are you ready to build the future of supply chain? At Gather AI, we're not just creating software; we're pioneering a new era of warehouse intelligence. We've developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining "on-time, in full" delivery. If you're looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We're leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About You

As a Principal Systems Engineer at Gather AI you will be a technical leader, driving the development and integration of cutting-edge autonomous and passive sensing systems, bridging the gap between product vision, complex system requirements, hardware implementation, and real-world performance.

What You’ll Do

• Take full technical ownership of the design, architecture, and integration of the autonomous data gathering systems in logistics and material handling environments.
• Collaborate with Product Management, Customers, and cross-functional engineering teams (e.g., Software, Hardware, Cloud, Test) to negotiate and finalize system boundaries and interfaces.
• Serve as a technical leader, mentoring less experienced engineers and setting the standard for systems engineering best practices. 
• Possess specific, in-depth knowledge of hardware implementation and integration challenges for both active robotic components (e.g., actuators, controllers) and passive sensing modalities (e.g., RGB cameras, depth cameras).
• Drive trade-off analyses, risk assessment, and mitigation planning for critical system elements.

Requirements

• BS, MS, or PhD in Systems Engineering, Robotics, Mechanical or Electrical Engineering, Computer Science, or a related field.
• 10-15 years of experience in systems engineering, with a significant focus on complex hybrid hardware/software systems.
• Demonstrated technical ownership of major cross-functional product development initiatives.
• Comfort with complex algorithms in the robotics domain - finding, evaluating, and applying algorithms in mixed language (C++/Python) systems.
• Understanding of considerations regarding mechanical mounts, power and RF, and ingress protection.
• Expertise in the integration and performance characterization of passive sensing systems (e.g., perception, localization, mapping) and/or active robotic systems (e.g., navigation, control).
• Proven track record of defining and verifying system requirements for complex autonomous systems.
• Strong communication skills, particularly in writing documents that identify critical requirements and explain challenging problems clearly.
• Persistence and calm leadership in an agile work environment.

About Us

Are you ready to build the future of the supply chain? At Gather AI, we’re not just creating software; we’re pioneering a new era of warehouse intelligence. We’ve developed a groundbreaking, vision-powered platform that uses autonomous drones and existing equipment to capture real-time data, completely digitizing workflows that have historically been manual and error-prone. This means facilities operate smarter, safer, and more efficiently, ultimately redefining “on-time, in full” delivery.

If you’re looking for an opportunity to contribute to truly transformative technology and make a significant impact in a vital industry, Gather AI is the place for you. We’re leading the charge in the rapidly evolving robotics industry, and we invite you to join us in reshaping the global supply chain, one intelligent warehouse at a time.

About the Team

This role sits at the intersection of our Autonomy, Machine Learning, Hardware, and Product teams. You will collaborate with engineers across drone, MHE Vision, and embedded systems, partner with Product on scanning accuracy requirements, and work with Hardware and Operations on camera mounting, lighting, and real-world warehouse deployment.

About the Role

We are seeking a Staff Robotics Engineer - Perception to take full technical ownership of one of Gather AI's two production platforms — our drone-based inventory scanning system or our MHE Vision product — deployed today in customer warehouses. You'll bring systems-level rigor to a platform that already works, with a mandate to make it faster to deploy, easier to operate, and more reliable at scale. 

This is a high-ownership, high-impact role, critical to the quality of every scan our system performs. You will drive technical direction and deliver measurable impact on production systems serving real customers.

What You’ll Do

• Own the camera and imaging subsystem audit across MHEV and Modal: characterize existing performance (barcode decode rates, read distances, motion blur impact) and identify top bottlenecks
• Evaluate and select camera and sensor hardware — specifying resolution, sensor size, lens selection, and exposure control for industrial warehouse environments
• Implement and tune auto-exposure, gain control, and lighting strategies for variable warehouse lighting conditions, including motion blur mitigation for moving platforms
• Develop image quality metrics and production monitoring to maintain system performance as deployments scale
• Collaborate with the ML team to ensure perception model inputs meet training and inference quality requirements; contribute to next-generation capabilities such as damage detection and label reading
• Work with the hardware team on camera mounting, vibration/damping, and lens placement to optimize system-level performance

What You’ll Need

• 5+ years of experience in machine vision, imaging systems, or perception engineering
• Deep expertise in camera systems: sensor selection, lens specification, resolution analysis, pixels-on-target calculations, and exposure control for industrial applications
• Hands-on experience with motion blur analysis and mitigation — rolling vs global shutter trade-offs, exposure budgeting relative to platform velocity
• Strong Python and C++ proficiency with OpenCV and camera SDK experience (FLIR, Lucid, Basler, or similar); familiarity with GigE Vision or USB3 Vision standards
• BS or MS in Electrical Engineering, Optics, Physics, Computer Science, or a related field

Nice to Have

• Experience with drone or robotics perception systems (gimbal stabilization, triggering, onboard compute constraints)
• Optical design or lens selection experience (MTF analysis, depth of field, distortion characterization)
• Edge compute and embedded vision experience (NVIDIA Jetson, FPGA-based image processing)
• Familiarity with classical and deep learning perception algorithms and how image quality affects model performance

Latitude AI (lat.ai) develops automated driving technologies, including L3, for Ford vehicles at scale. We’re driven by the opportunity to reimagine what it’s like to drive and make travel safer, less stressful, and more enjoyable for everyone.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to making a real, positive impact on the driving experience for millions of people. 

As a Ford Motor Company subsidiary, we operate independently to develop automated driving technology at the speed of a technology startup. Latitude is headquartered in Pittsburgh with engineering centers in Dearborn, Mich., and Palo Alto, Calif.

Meet the team:

The Enterprise Cyber Security team is focused on ensuring the resilience of our corporate environment with focus on protection of our corporate systems, IP, and employee data. We are a close-knit team with strong cross-functional roles in the company.

As a Cyber Security Engineer, you will be the hands-on technical lead securing our Infrastructure and assets (Servers, Client Endpoints, VMs, etc…) with a focus on Data Protection/Loss Prevention (DLP/CASB/MDM, etc…), and Identity Management Solutions (Entra/AD/LDAP/MFA). You will be backing up others on the team including Incident Response and Vulnerability Management. You should have a deep understanding of infrastructure and solutions that support management of assets and the operations depending on it, including our software/hardware/network engineering, fleet operations requirements, and administrative functions. You will use your knowledge and experience to design, implement, measure, and continuously improve our security posture and tooling. 

What you’ll do: 

• Plan for, execute, and follow through on projects and engagements independently or with little guidance
• Manage and audit our Identity Provider Solutions (Entra, LDAP preferred)
• Apply best practices in software engineering, delivering projects on time, on budget, and with excellent quality and security configurations
• Create new deployments and architecture designs and review existing ones looking for design flaws, security improvements, and advocating for stronger security controls that meet functional and operational needs
• Work hand-in-hand with the IT and Product teams to review, research, design and develop security solutions that enable productivity, but maintain security
• Engage actively in software selection and deployment initiatives to assess and onboard security and other technical solutions for endpoints, development and production environments 
• Perform Security Assessments and Audits - Documenting findings, implementing remediation, or drafting Action Plans for remediation/mitigation
• Implement automation and orchestration aspects of security processes and tooling to integrating with APIs and applications/workflows across the organization and in our SIEM (Splunk and Apigee experience preferred)
• Identify, Develop, and deliver dashboards and report metrics on the status of the Cyber Security posture, and develop dashboards, reports, and define metrics for cross-functional teams
• Moderate and contribute to deployments and administrative controls that contribute to:
• Proactive monitoring, analysis, and correcting system security issues
• Development of scripts to automate, perform security checks, and develop tools to enhance support of the infrastructure and endpoint systems
• Implement and deploy solutions to protect infrastructure and Intellectual Property
• Developing playbooks/runbooks, operational and troubleshooting documentation for use internally and with external MDR providers
• Manage and deploy solutions for Data Protection consisting of MDM, EDR, DLP, CASB, and system hardening/compliance
• Provide ongoing support for various Incident, Vulnerability, and Security event workflows

What you'll need to succeed:

• Minimum requirements Bachelor's degree in Computer Engineering, Computer Science, Cyber Security or a related field and 2+ years of relevant experience, Master's degree, or PhD
• Relevant hands-on experience deploying and administering solutions as a Cyber Security Engineer and Operational Administrator
• 2+ years of related experience Incident Response management and assessing the risk/severity rating of incidents and exposures
• 2+ years Hands-on experience with tooling in the Entra, Intune, EDR, DLP, CASB, and Splunk SOAR/Enterprise Security and Logging/Alerting tools and Compliance/Response space
• Experience with MacOS, Linux, and Windows Systems Administration using configuration management software and tooling to manage systems across a large and distributed environments
• Strong understanding of Cyber Security Standards (ISO27001, NIST 800-53, CIS Benchmarks)
• Ability and experience with automation of Security Standards and Compliance scanning and configuration hardening, and detections for non-compliance
• Must have demonstrated proficiency and strength in verbal, written, presentation, and communications skills, including technical diagramming, interactions cross-functionally with teams outside of the Cyber Security Team
• High proficiency in Tooling for Identity Management and Authentication Solutions, Mobile Device Management, and Data Protection Tooling (Entra, Intune, Endpoint Agents)
• Proficiency in scripting languages, including Bash, Python, Go, or Java to create production level services and tools
• Proficiency in using Infrastructure as Code (IaC) to automate the deployment of Cyber Security Solutions. E.g. Terraform, Ansible, or others
• Ability to grasp new technologies quickly, prioritize and multitask on multiple responsibilities
• Hands-on Experience with patching and hardening Linux, MacOS, and Windows Systems (clients and servers) using standards such as the Center for Internet Security (CIS) Critical Security Controls 
• Proficient in Network Protocols and Host Firewall Management, with hands-on experience in configuration and optimization to ensure infrastructure network security at the host level and at perimeters
• Critical thinking and a holistic view of Cyber Security with ability to balance security requirements with mission needs and collaboration across teams
• Exceptional organizational and time management skills demonstrated through adept autonomy, creation of timelines, scope and priorities,  independent work, collaborative teamwork, and a professional demeanor
• Strong experience with architecting/deploying scalable security services and workloads in the infrastructure and endpoint space. Minimizing impact with regard to functional impact on compute workloads running on CPUs, GPUs, and Memory utilization
• Understand engineering design limitations and provide guidance for teams to secure their deployments to achieve desired performance in budget and on time
• An Independent take-charge attitude while being open-minded, creatively thinking, willing to take calculated risks, and make informed decisions
• A sense of comradery, compassion, and unparalleled passion/energy

What we offer you:

• Competitive compensation packages
• High-quality individual and family medical, dental, and vision insurance
• Health savings account with available employer match
• Employer-matched 401(k) retirement plan with immediate vesting
• Employer-paid group term life insurance and the option to elect voluntary life insurance
• Paid parental leave
• Paid medical leave
• Unlimited vacation
• 15 paid holidays
• Daily lunches, snacks, and beverages available in all office locations
• Pre-tax spending accounts for healthcare and dependent care expenses
• Pre-tax commuter benefits
• Monthly wellness stipend
• Adoption/Surrogacy support program
• Backup child and elder care program
• Professional development reimbursement
• Employee assistance program
• Discounted programs that include legal services, identity theft protection, pet insurance, and more
• Company and team bonding outlets: employee resource groups, quarterly team activity stipend, and wellness initiatives

Learn more about Latitude’s team, mission and career opportunities at lat.ai!

The expected base salary range for this full-time position in California is $133,280 - $199,920 USD. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education, and skill level. Latitude employees are also eligible to participate in Latitude’s annual bonus programs, equity compensation, and generous Company benefits program, subject to eligibility requirements.

Candidates for positions with Latitude AI must be legally authorized to work in the United States on a permanent basis. Verification of employment eligibility will be required at the time of hire.

We are an Equal Opportunity Employer committed to a culturally diverse workforce. All qualified applicants will receive consideration for employment without regard to race, religion, color, age, sex, national origin, sexual orientation, gender identity, disability status or protected veteran status.

About The Role

As a Staff Software Engineer on the AI team, you will architect and build production-quality teleoperation systems that enable Digit to execute complex whole-body manipulation tasks in real-world environments. You will work closely with AI, controls, hardware, and operations teams to create a scalable platform for high-quality human demonstration data collection. Your work will directly enable our ability to scale up the world's first production humanoid robot fleet and revolutionize the labor market.

About The Work

• Own the end-to-end architecture of the teleoperation system, from operator input through real-time robot execution, ensuring low latency, predictable behavior, and clear system boundaries
• Integrate and optimize real-time control, streaming, and communication paths to meet measurable latency and bandwidth targets
• Design and implement scalable teleoperation interfaces, including VR, motion capture, and other modalities, to enable high-quality manipulation and locomotion demonstrations
• Develop comprehensive validation strategies in simulation and on hardware, including performance benchmarks, fault handling, and regression testing
• Analyze teleoperation and demonstration data to improve operator efficiency, system responsiveness, and task success rates
• Anticipate future robot hardware and sensor changes, and design systems that can adapt to new interfaces and capabilities with minimal architectural disruption

About You

• 8+ years of experience in robotics or real-time systems, with a demonstrated track record of delivering reliable, production-quality software
• Deep understanding of real-time control systems, motion retargeting, and rigid body dynamics
• Experience designing low-latency communication and streaming systems for real-time applications
• Strong systems intuition with the ability to trace performance issues across software, networking, and hardware boundaries
• Strong analytical and debugging skills, with a data-driven approach to performance validation and system reliability
• Hands-on experience integrating human input systems such as VR, motion capture, wearable devices, or other operator interfaces
• Excellent communication skills and the ability to collaborate effectively across AI, controls, hardware, and operations teams

Bonus Qualifications

• Experience building applications with real-time rendering or XR frameworks such as Unity, Unreal, Godot, SteamVR, or OpenXR
• Experience with advanced 3D visualization techniques such as neural radiance fields, Gaussian splatting, or other scene reconstruction methods
• Familiarity with large-scale data collection pipelines for learning from demonstration

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

Agility Robotics is deploying humanoid robots that are solving real-world challenges in logistics and manufacturing. Perceiving and understanding the world is critical to Digit’s success in these applications. The Perception team is looking for a staff machine learning engineer to own the design and development of object detection and tracking algorithms.

Responsibilities:

• As a technical lead, you will own the architecture and technical roadmap for object perception systems used by the robot in production
• Design, develop, and deploy machine learning algorithms for multi-object detection, scene understanding, and 6-DoF object pose estimation
• Evaluate and drive adoption of state-of-the-art perception models
• Promote best practices in architecture, design, and testing to deliver high-quality, scalable software
• Optimize deep neural networks and associated data processing to run efficiently on embedded systems
• Collaborate with navigation, manipulation and hardware teams to align perception capabilities with product requirements

Requirements:

• 5+ years of experience deploying machine learning-based object detection algorithms on mobile robots with at least 2 years of experience in a technical leadership role
• Proficiency in related technical areas such as (but not limited to) deep convolutional neural networks, multi-object tracking, data association, supervised learning and pose estimation
• Strong mathematical fundamentals in linear algebra and numerical optimization and familiarity with core geometric concepts in computer vision
• Familiarity with common computer vision and machine learning libraries such as (but not limited to) PyTorch, OpenCV, NumPy, etc.
• Experience designing and optimizing algorithms for efficient execution across CPU and GPU architectures
• Experience with MLOps such as (but not limited to) data annotation services, data storage, model evaluation tools, and model deployment
• Publications in your field (CVPR, ICCV, RSS, ICRA preferred)

Bonus Qualifications:

• Experience using YOLO, Faster/Mask R-CNN
• Experience developing ML models for 3 or 6 dof pose estimation

This a hybrid position based out of one of our Salem, Pittsburgh, or Fremont offices.

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to: market location, job-related knowledge, skills, and experience. This range may change based on geographical location and may be modified in the future.

About Us

We are on a mission to accomplish the impossible and build a safer future of autonomous and robotic machines. We are looking for a growth-minded and dynamic Infrastructure Engineer - Hardware-In-the-Loop (HIL) who embodies our values of excellence, ownership, collaboration, and effective communication.

Role Overview

We are seeking a Senior Engineer focused on building and scaling HIL test infrastructure and automation platforms. This role goes beyond test execution — you will design multi-bench systems, CI/CD-driven workflows, and reliable lab infrastructure to enable efficient, repeatable validation of Fort products.

Responsibilities

• Design and scale Hardware-in-the-Loop (HIL) benches for system and device-level validation
• Build infrastructure for multi-bench orchestration (scheduling, parallel execution, resource management)
• Build and manage DevOps workflows for test infrastructure, including pipeline automation, environment provisioning, and artifact management.
• Design and integrate CI/CD pipelines for hardware-based testing
• Build containerized (like Docker) environments for reproducible test execution
• Develop systems to control hardware programmatically (power, connectivity, devices)
• Improve lab infrastructure, fixtures, and test environments for scalability and reliability
• Build logging, metrics, and observability systems for debugging and traceability
• Collaborate with firmware, cloud, and hardware teams to resolve system-level issues
• Mentor engineers and drive best practices for scalable test infrastructure

Qualifications

• Bachelor’s or Master’s in Electrical Engineering, Computer Engineering, Computer Science, or related discipline preferred
• 5+ years of experience in embedded systems, robotics, or hardware-software systems
• Strong experience with HIL/SIL systems or test infrastructure
• Proficiency in Python for automation/framework development
• Experience designing automation systems at scale (multi-device, multi-environment, or distributed systems)
• Strong experience with CI/CD systems (GitLab, Jenkins, or similar), including pipeline design and automation workflows
• Experience with containerization technologies (Docker) and building reproducible development and test environments
• Familiarity with DevOps practices and scalable system design
• Experience with embedded communication protocols (Ethernet, CAN, BLE, Wi-Fi)
• Strong debugging skills across hardware and software systems
• Ability to design modular, maintainable systems and work cross-functionally

Preferred

• Experience with distributed systems or orchestration platforms
• Experience with cloud/logging tools (Azure, Grafana, etc.)
• Knowledge of safety standards (IEC 61508, ISO 26262)
• Hands-on hardware/fixture design experience
• Interest in applying AI/ML in daily engineering workflows

Position Overview

We are seeking an experienced IT Generalist to manage and support our IT infrastructure and security systems. This role is essential in supporting our high-tech environment, including our advanced robotics and AI research. The ideal candidate will be a proactive problem-solver who is adept at managing both hardware and software resources, ensuring smooth IT operations, and safeguarding our digital and physical assets.

Responsibilities

• Manage and troubleshoot IT infrastructure, including compute resources like GPU clusters and cloud environments.
• Administer access controls and implement security measures across all software platforms.
• Maintain and update IT equipment inventory, and oversee the IT setup for new employees.
• Develop and enforce IT policies to secure our robotics technology and intellectual property.
• Collaborate with technical teams to resolve IT issues and support the deployment and operation of advanced robotic systems.
• Ensure that our company website and internal tools are maintained and functional.

Preferred Qualifications

• Previous work experience as a: Systems Administrator, Network Administrator, Linux Administrator, Database Administrator, Site Reliability Engineer (SRE), Systems Engineer, Software Engineer, DevOps Engineer, Network Engineer, or similar.
• Solid knowledge of system administration, network administration, and cloud infrastructure.
• Experience with enterprise security.
• Excellent problem-solving skills and the ability to work autonomously.

Efficient is seeking a  RTL-DV CAD Lead Engineer to own and advance the EDA flow infrastructure that powers our RTL design and  design verification (DV) teams. In this role you will define methodology, build automation, and provide hands-on flow support across the entire pre-silicon development cycle — from RTL synthesis and lint to UVM testbench execution. You will work at the intersection of EDA tool expertise, scripting/infrastructure engineering.

If you enjoy making engineers wildly productive, love root-causing weird build failures, and don’t mind occasionally wrestling with a vendor license server at 2am then this role is for you. Join our team and help us shape the future of computing at the edge and beyond!

Key Responsibilities

• Help develop CAD flows in close collaboration with  RTL designers for RTL design: lint (Spyglass/Jasper), CDC/RDC analysis, synthesis (Design Compiler/Genus), equivalence checking (Formality/Conformal), and static timing analysis.
• Develop and maintain simulation flows in collaboration with the DV team  for functional verification using leading simulators (VCS, Xcelium, Questa); manage compile, elaborate, and regression infrastructure.
• Define (in collaboration with the RTL/DV leads) RTL coding guidelines, lint rule policies, and waiver management processes.
• Design and implement build/regression automation frameworks using Python, Makefile, Tcl, and shell scripting; integrate with LSF/SLURM job schedulers for farm-efficient execution.
• Build and maintain CI/CD pipelines (Jenkins/GitLab CI) that gate RTL checkins on lint, CDC, and smoke-regression results.
• Help develop coverage collection and closure infrastructure: merge/analyze per-block and SoC-level coverage databases (VCS CM, Xcelium IMC) and publish dashboards to support sign-off decisions.
• Provide scripted infrastructure for test-list management, seed sweeps, and regression triage; reduce manual overhead through automation.
• Establish process for Soft-IP and Hard-IP downloads and versioning with the RTL/PD team,  VIP integration and BFM bring-up in partnership with DV lead.
• Ensure we have the latest tool versions for the complete RTL/DV EDA tool suite. Establish relationships with EDA vendors to stay on top of licenses and ensure we have the appropriate license features and count available at any given time.
• Mentor junior CAD and DV engineers on flow best practices, scripting techniques, and EDA tool usage.

Required Qualifications

• 8+ years of hands-on CAD or DV infrastructure engineering experience in a semiconductor design environment.
• Proven ownership of simulation, lint, CDC  for complex RTL blocks or SoC-level designs.
• Strong scripting proficiency in Python and Tcl; experience with Makefile-based or equivalent build systems..
• Experience with at least two major commercial simulators (VCS, Xcelium, Questa) and/or formal tools (JasperGold, VC Formal, Conformal).
• Familiarity with job schedulers (LSF, SLURM) and version control systems (Git).
• Strong communication skills; ability to translate complex flow issues into actionable guidance for design engineers.