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 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:

This position reports directly into the Controller. The Account’s Payable team mission is to provide customer focused services to the entire organization and you will be responsible for oversight of accounts payable, accounts receivable and the Company’s travel and expense program.

What You'll Be Doing:

•     Continue to build and seek opportunities for process efficiency to establish a world class Accounts Payable organization that can efficiently scale with Motional’s hyper growth.
•     Handles escalations of day-to-day accounts payable operations in all areas: PO and Non-PO invoice processing, payment holds, payment cycles, payment processing, expense reimbursements and vendor account reconciliations.
•     Understand the full procure-to-pay cycle to quickly identify the source of bottlenecks, problems and drive issues to resolution.
•     Conduct month-end, quarter-end and year-end close activities in support of Motional’s Finance organization.
•     Ensure accounts payable operations comply with statutory requirements, Company policies, processes, procedures, and internal controls within a global organization that includes Singapore and the United States.
•     Oversee and provide guidance for the ongoing day-to-day activities and longer-term strategic direction of the department including automation and process streamlining initiatives.
•     Ensure Company departments and business partners have a clear understanding of accounts payable services, policies, and company approval levels.
•     Develop collaborative relationships acting as a well-respected, trusted partner cross functionally with key stakeholders.
•     Develop supplier/vendor relationships to quickly resolve payment issues, create and execute a payment strategy, and ensure vendor/supplier alignment with the direction of the company.
•     Establish key metrics and reporting cadence for Accounts Payable and drive initiatives to scale the organization.
•     Manage, coordinate, and support special projects as needed.
•     Problem solve, prioritize multiple projects and adhere to business-critical deadlines
•     Support annual audit as needed
•     Partner and facilitate communications with direct and indirect procurement teams for vendor onboarding and maintenance, T&E administration
  
  

What We're Looking For:

•     BA/BS in Accounting, Finance or related field
•     8+ years of accounts payable professional experience including several in a management or supervisory role
•     Excellent judgment and creative problem-solving skills.
•     Exceptional written, oral, interpersonal, and presentation skills and the ability to effectively interface with management and teams across the organization.
•     Ability to operate as an effective tactical as well as strategic thinker.
•     Can do attitude, can roll up the sleeves and dive into the details quickly
•     Comfort to brief senior executives on results, obstacles and escalations
•     Bias for action, accountability and spirit of service
  
  

Why You Should Join Us:

•   Fast paced environment in a competitive AV industry with opportunity for measurable contributions towards company KPI’s and cross-functional exposure and visibility 
•   Ability to take ownership over the Accounts Payable team as we build for scale and commercialization in late 2026 
  
  

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

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

Mission Summary:

As a Staff Engineer within the Platform Engineering team, you will be a hands-on technical leader driving the evolution of Motional's global cloud and hybrid infrastructure. Operating as a senior individual contributor, you'll tackle our hardest platform problems directly — designing systems, creating code, and setting technical direction for initiatives that span multiple teams. Your work will help transform our R&D environment into a hardened, cost-efficient, and scalable commercial backbone, and ensure our internal platforms deliver the developer velocity required for rapid AV deployment.

What you'll be doing:

• Design and build major components of our cloud architecture — including networking, storage, compute abstraction layers. You'll own the technical design end-to-end and create code where it matters most
• Drive technical evolution of our Kubernetes-based developer platform. Identify the highest-leverage improvements to scalability, cost attribution, access control, and developer ergonomics — then design and implement them to reduce configuration complexity and accelerate engineering velocity
• Raise the reliability bar across Platform Engineering. Define and implement standards for SLIs, SLOs, observability, and failover, and partner with peer teams to roll them out across platform-layer services
• Drive FinOps practices — cost visibility, attribution, accountability as well as optimization recommendations
• Design and ship AI-native developer experiences by integrating LLM-powered tooling into CI, build systems, monitoring platforms, and local development workflows to remove friction and boost engineering throughput
  
  

What we're looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 9 years in Software or Infrastructure Engineering, with significant experience in a senior IC capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (Operators (Crossplane, ArgoWorkflow/Airflow, KubeRay), Kubecost/OpenCost, Service Mesh, GitOps and other CNCF projects)
• Proven track record of designing or migrating complex workloads between on-prem data centers and major cloud providers (AWS, GCP, other)
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus/VictoriaMetrics, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff
  
  

Bonus points (not required):

• Proven expertise in CI/CD orchestration, build systems (Bazel, RBE), frameworks
• Prior experience with large-scale machine learning training pipelines
• Experience leading technical projects in a globally distributed team
• Open-source contributions to Kubernetes, observability, or infrastructure tooling ecosystems

Mission Summary:

We are seeking a Verification and Validation (V&V) Lead to spearhead efforts for the Perception subsystem of our autonomy stack. Reporting directly to the Head of Perception, this critical role is responsible for the full spectrum of efforts required to close the safety case for the perception subsystem, enabling our driverless commercial launch and subsequent product expansions.

This hybrid role demands broad experience in the self-driving field, with specific competencies in: test engineering, systems and safety, data analytics and reporting, simulation technology, and leveraging AI for workload automation and insight generation. Success in this highly collaborative role also requires exceptional written and verbal communication, leadership, cross-team influence, and a consistent ability to prioritize work and deliver results.

Key Responsibilities:

• Requirements Driven Development / Test Driven Development
• Influence requirements from the perspective of problem understanding, covariate coverage, and testing capabilities/challenges.
• Educate perception engineers and be a champion for V&V best practices.
  
  
• Problem Definition and Performance Analysis
• Collaborate with autonomy and systems engineers to establish problem taxonomies and identify critical performance covariates.
• Identify or define appropriate metrics.
• Create dashboards and automate reporting.
  
  
• Perception V&V Strategy
• Establish coverage targets and identify data/testing gaps.
• Validate the test strategy and provide early feedback to developers.
• Create actionable test plans involving a spectrum of test modalities.
• Create critical tests as-needed, work cross-team to scale test creation to achieve coverage targets.
  
  
• Test Technologies
• Understand the limitations of existing tools and simulation technologies and how they impact our coverage plans.
• Advocate for engineering work to address testing and automation limitations.
• Find creative ways to get the desired signals when a straightforward approach is deemed infeasible.
  
  
• System/Subsystem Performance Boundaries
• Be a bridge between Perception and the “Systems Readiness and Performance” organization. Act as the primary point of contact between the organizations.
• Advocate for, and adopt, common processes, technology, and terminology to ensure subsystem and system level evaluations work seamlessly together.
• Ensure that we understand the system-level impact of a perception failure mode and communicate this effectively across the entire organization.
  
  

Required Qualifications:

• Education and Experience
• Bachelor's degree in a STEM field (preferred).
• Experience leading Verification and Validation (V&V) for a safety-critical product.
• V&V experience specifically with a self-driving vehicle (strongly preferred).
  
  
• Domain Expertise
• General knowledge of the self-driving vehicle software stack.
• Understanding the different types of simulation technologies used in autonomy development.
• Expertise in creating and executing V&V test strategies.
• Expertise in test set creation, test organization (tagging, requirements and deficiency linking), and structured reporting.
• Strong understanding of how performance analysis informs risk assessment, and acts as the cornerstone for “go/no-go” decisions.
• Understanding of basic descriptive statistics.
  
  
• Programming & Tools
• Proficiency in Python for light scripting, database queries, and automation.
• Familiarity with common dashboarding software.
• Familiarity with AI/Agentic coding tools to accelerate workloads.
• Experience using common software tools such as version control (Git) and build automation (Buildkite, Jenkins).
  
  
• Soft Skills
• Excellent written and verbal communication skills.
• Demonstrated ability in collaboration, leadership, innovation, and creativity.
• A track record of reliability, trustworthiness, and delivering impact.
• Ability to frame safety discussions within a grounded risk assessment framework.
  
  

Preferred Qualifications:

• Entrepreneurial experience or other evidence of being self-driven, adaptable, and results-oriented.
• Patents or other evidence of innovation and creativity.
  
  

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:

We are seeking a Verification and Validation (V&V) Lead to spearhead efforts for the Perception subsystem of our autonomy stack. Reporting directly to the Head of Perception, this critical role is responsible for the full spectrum of efforts required to close the safety case for the perception subsystem, enabling our driverless commercial launch and subsequent product expansions.

This hybrid role demands broad experience in the self-driving field, with specific competencies in: test engineering, systems and safety, data analytics and reporting, simulation technology, and leveraging AI for workload automation and insight generation. Success in this highly collaborative role also requires exceptional written and verbal communication, leadership, cross-team influence, and a consistent ability to prioritize work and deliver results.

Key Responsibilities:

• Requirements Driven Development / Test Driven Development
• Influence requirements from the perspective of problem understanding, covariate coverage, and testing capabilities/challenges.
• Educate perception engineers and be a champion for V&V best practices.
  
  
• Problem Definition and Performance Analysis
• Collaborate with autonomy and systems engineers to establish problem taxonomies and identify critical performance covariates.
• Identify or define appropriate metrics.
• Create dashboards and automate reporting.
  
  
• Perception V&V Strategy
• Establish coverage targets and identify data/testing gaps.
• Validate the test strategy and provide early feedback to developers.
• Create actionable test plans involving a spectrum of test modalities.
• Create critical tests as-needed, work cross-team to scale test creation to achieve coverage targets.
  
  
• Test Technologies
• Understand the limitations of existing tools and simulation technologies and how they impact our coverage plans.
• Advocate for engineering work to address testing and automation limitations.
• Find creative ways to get the desired signals when a straightforward approach is deemed infeasible.
  
  
• System/Subsystem Performance Boundaries
• Be a bridge between Perception and the “Systems Readiness and Performance” organization. Act as the primary point of contact between the organizations.
• Advocate for, and adopt, common processes, technology, and terminology to ensure subsystem and system level evaluations work seamlessly together.
• Ensure that we understand the system-level impact of a perception failure mode and communicate this effectively across the entire organization.
  
  

Required Qualifications:

• Education and Experience
• Bachelor's degree in a STEM field (preferred).
• Experience leading Verification and Validation (V&V) for a safety-critical product.
• V&V experience specifically with a self-driving vehicle (strongly preferred).
  
  
• Domain Expertise
• General knowledge of the self-driving vehicle software stack.
• Understanding the different types of simulation technologies used in autonomy development.
• Expertise in creating and executing V&V test strategies.
• Expertise in test set creation, test organization (tagging, requirements and deficiency linking), and structured reporting.
• Strong understanding of how performance analysis informs risk assessment, and acts as the cornerstone for “go/no-go” decisions.
• Understanding of basic descriptive statistics.
  
  
• Programming & Tools
• Proficiency in Python for light scripting, database queries, and automation.
• Familiarity with common dashboarding software.
• Familiarity with AI/Agentic coding tools to accelerate workloads.
• Experience using common software tools such as version control (Git) and build automation (Buildkite, Jenkins).
  
  
• Soft Skills
• Excellent written and verbal communication skills.
• Demonstrated ability in collaboration, leadership, innovation, and creativity.
• A track record of reliability, trustworthiness, and delivering impact.
• Ability to frame safety discussions within a grounded risk assessment framework.
  
  

Preferred Qualifications:

• Entrepreneurial experience or other evidence of being self-driven, adaptable, and results-oriented.
• Patents or other evidence of innovation and creativity.
  
  

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:

We are seeking a Verification and Validation (V&V) Lead to spearhead efforts for the Perception subsystem of our autonomy stack. Reporting directly to the Head of Perception, this critical role is responsible for the full spectrum of efforts required to close the safety case for the perception subsystem, enabling our driverless commercial launch and subsequent product expansions.

This hybrid role demands broad experience in the self-driving field, with specific competencies in: test engineering, systems and safety, data analytics and reporting, simulation technology, and leveraging AI for workload automation and insight generation. Success in this highly collaborative role also requires exceptional written and verbal communication, leadership, cross-team influence, and a consistent ability to prioritize work and deliver results.

Key Responsibilities:

• Requirements Driven Development / Test Driven Development
• Influence requirements from the perspective of problem understanding, covariate coverage, and testing capabilities/challenges.
• Educate perception engineers and be a champion for V&V best practices.
  
  
• Problem Definition and Performance Analysis
• Collaborate with autonomy and systems engineers to establish problem taxonomies and identify critical performance covariates.
• Identify or define appropriate metrics.
• Create dashboards and automate reporting.
  
  
• Perception V&V Strategy
• Establish coverage targets and identify data/testing gaps.
• Validate the test strategy and provide early feedback to developers.
• Create actionable test plans involving a spectrum of test modalities.
• Create critical tests as-needed, work cross-team to scale test creation to achieve coverage targets.
  
  
• Test Technologies
• Understand the limitations of existing tools and simulation technologies and how they impact our coverage plans.
• Advocate for engineering work to address testing and automation limitations.
• Find creative ways to get the desired signals when a straightforward approach is deemed infeasible.
  
  
• System/Subsystem Performance Boundaries
• Be a bridge between Perception and the “Systems Readiness and Performance” organization. Act as the primary point of contact between the organizations.
• Advocate for, and adopt, common processes, technology, and terminology to ensure subsystem and system level evaluations work seamlessly together.
• Ensure that we understand the system-level impact of a perception failure mode and communicate this effectively across the entire organization.
  
  

Required Qualifications:

• Education and Experience
• Bachelor's degree in a STEM field (preferred).
• Experience leading Verification and Validation (V&V) for a safety-critical product.
• V&V experience specifically with a self-driving vehicle (strongly preferred).
  
  
• Domain Expertise
• General knowledge of the self-driving vehicle software stack.
• Understanding the different types of simulation technologies used in autonomy development.
• Expertise in creating and executing V&V test strategies.
• Expertise in test set creation, test organization (tagging, requirements and deficiency linking), and structured reporting.
• Strong understanding of how performance analysis informs risk assessment, and acts as the cornerstone for “go/no-go” decisions.
• Understanding of basic descriptive statistics.
  
  
• Programming & Tools
• Proficiency in Python for light scripting, database queries, and automation.
• Familiarity with common dashboarding software.
• Familiarity with AI/Agentic coding tools to accelerate workloads.
• Experience using common software tools such as version control (Git) and build automation (Buildkite, Jenkins).
  
  
• Soft Skills
• Excellent written and verbal communication skills.
• Demonstrated ability in collaboration, leadership, innovation, and creativity.
• A track record of reliability, trustworthiness, and delivering impact.
• Ability to frame safety discussions within a grounded risk assessment framework.
  
  

Preferred Qualifications:

• Entrepreneurial experience or other evidence of being self-driven, adaptable, and results-oriented.
• Patents or other evidence of innovation and creativity.
  
  

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 Talent Acquisition Team recruits and supports world class talent. We are actively looking for a Talent Acquisition Sourcer to support all areas of technical hiring within our Autonomy Department. We are hoping you’ll be interested to join us!

What you’ll be doing:

• Research and execute to identify and attract talented technical individuals at all levels.
• Build long standing relationships with sourced candidates to best represent the Motional teams and culture
• Deep dive and cultivate difficult to find talent to join our teams
• Demonstrate expert knowledge of Motional’s roles, focusing on machine learning, software engineering and more technical capabilities.
• Provide a best in class candidate experience as the initial contact. 
• A drive to not only find talent, but create strategic ways to build long standing relationships with those that are not ready to join us today. 
  
  

What we’re looking for:

• 3+ year of relevant sourcing or recruiting experience/working with candidates and clients within Software Engineering functions
• ATS experience (Greenhouse preferred but not required)
• Experience using LinkedIn Recruiter and other sourcing tools.
• Strong ability to screen candidates for interest level and high level details.
• Strategic partner mindset with recruiting and clients
• Excellent communication and interpersonal skills
• BA/BS degree or equivalent practical experience
  
  

It's a bonus if you have:

• Experience sourcing for niche or highly technical roles in the AV industry
  
  

Why You Should Join Us:

• Motional fosters a culture of inclusion and learning. The Talent Acquisition team works in a collaborative based approach to fill an exceptionally high number of roles, in a short amount of time, with only the highest expectations of support and guidance to get the job done as a team. We celebrate the big wins, and we support and help guide/grow when there are losses. We hope you considering joining us on the mission to build and foster a world class organization within Motional.
  
  

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

Motional’s Talent Acquisition Team recruits and supports world class talent. We are actively looking for a Talent Acquisition Sourcer to support all areas of technical hiring within our Autonomy Department. We are hoping you’ll be interested to join us!

What you’ll be doing:

• Research and execute to identify and attract talented technical individuals at all levels.
• Build long standing relationships with sourced candidates to best represent the Motional teams and culture
• Deep dive and cultivate difficult to find talent to join our teams
• Demonstrate expert knowledge of Motional’s roles, focusing on machine learning, software engineering and more technical capabilities.
• Provide a best in class candidate experience as the initial contact. 
• A drive to not only find talent, but create strategic ways to build long standing relationships with those that are not ready to join us today. 
  
  

What we’re looking for:

• 3+ year of relevant sourcing or recruiting experience/working with candidates and clients within Software Engineering functions
• ATS experience (Greenhouse preferred but not required)
• Experience using LinkedIn Recruiter and other sourcing tools.
• Strong ability to screen candidates for interest level and high level details.
• Strategic partner mindset with recruiting and clients
• Excellent communication and interpersonal skills
• BA/BS degree or equivalent practical experience
  
  

It's a bonus if you have:

• Experience sourcing for niche or highly technical roles in the AV industry
  
  

Why You Should Join Us:

• Motional fosters a culture of inclusion and learning. The Talent Acquisition team works in a collaborative based approach to fill an exceptionally high number of roles, in a short amount of time, with only the highest expectations of support and guidance to get the job done as a team. We celebrate the big wins, and we support and help guide/grow when there are losses. We hope you considering joining us on the mission to build and foster a world class organization within Motional.
  
  

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

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

This role is hybrid from our Pittsburgh office and requires two in-office days per week, ideally Tuesday and Thursday.

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

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

The ML Data Service team is seeking a highly experienced and motivated Staff Tech Lead Manager (TLM) to lead the development and operation of our core machine learning data infrastructure. This critical role requires a blend of deep technical expertise in machine learning systems, large-scale data processing, and proven leadership ability to manage both individual contributors and technical direction.

The ML Data Service team is responsible for providing reliable, high-quality, and easily accessible data for all ML use cases. As owners of the "Data Engineering" phase of the ML lifecycle, they manage the most critical input to any ML system: the data itself. Our infrastructure supports hundreds of data pipelines and petabytes of data, directly enabling the success of our flagship products.

What You'll Do

Technical Leadership and Strategy

• Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
• Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
• Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
• Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
• Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.

Management and Team Growth

• Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
• Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
• Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
• Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.

Collaboration and Execution

• Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
• Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
• Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.

What We're Looking For

• Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
• 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
• 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manger experience  of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
• Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
• Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.

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

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

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.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe 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 without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

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 Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional’s driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.

What You'll Do:

• Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
• Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
• Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
• Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
• Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
• Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.
  
  

What We're Looking For (Must-Haves):

• BS or MS in Computer Science, Machine Learning, or a related field.
• Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
• Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
• Working knowledge of version control, unit testing, and basic software design patterns.
• Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
• A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
• A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.
  
  

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.
• Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)
  
  

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 is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

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.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe 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 without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Mission Summary:

Motional is seeking a Staff Front End Engineer expert for its Web Visualization Tooling team.  This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improve the performance and adaptability of our autonomous vehicle (AV) system.

What you'll be doing:

• Drive cross-team standards and best practices for web development
• Own cross team collaboration, ensuring deliveries are made on time and effectively
• Architect and scale a modern frontend ecosystem using React, TypeScript, and Vue.
• Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to align tooling with real-world workflows
• Build mission-critical UI systems used by a variety of internal customers.
• Design initiative experiences for complex, data-heavy workflows.
• Drive best practices around performance, scalability and maintainability
• Ship quickly and iterate in a product driven environment.
  
  

What we're looking for:

• Desire to design and build user-facing visual applications, and a passion for good UX.
• Strong proficiency in React, Typescript and modern frontend architecture
• Proficiency in Vue
• Strong product sense with a focus on UX and usability.
• Ability to work with high ownership and autonomy.
• Ability to work autonomously and independently, and to drive development initiatives with little oversight. High aptitude for learning and organization skills.
• Great interpersonal skills and ability to mentor and (on occasion) delegate to other engineers at various levels of relative seniority.
• A well-established technical design and documentation habit
• Capability to work directly with customers to identify foundational needs and provide solutions.
  
  

Bonus Points(not required): 

• Demonstrated project management expertise / advanced hands-on understanding of project management agility and operational excellence.
• A love for the continuous delivery of value.
• Exposure to backend systems (Node, Python)
• Experience in Game Development or 3D Visualization

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 is seeking a Staff Front End Engineer expert for its Web Visualization Tooling team.  This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improve the performance and adaptability of our autonomous vehicle (AV) system.

What you'll be doing:

• Drive cross-team standards and best practices for web development
• Own cross team collaboration, ensuring deliveries are made on time and effectively
• Architect and scale a modern frontend ecosystem using React, TypeScript, and Vue.
• Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to align tooling with real-world workflows
• Build mission-critical UI systems used by a variety of internal customers.
• Design initiative experiences for complex, data-heavy workflows.
• Drive best practices around performance, scalability and maintainability
• Ship quickly and iterate in a product driven environment.
  
  

What we're looking for:

• Desire to design and build user-facing visual applications, and a passion for good UX.
• Strong proficiency in React, Typescript and modern frontend architecture
• Proficiency in Vue
• Strong product sense with a focus on UX and usability.
• Ability to work with high ownership and autonomy.
• Ability to work autonomously and independently, and to drive development initiatives with little oversight. High aptitude for learning and organization skills.
• Great interpersonal skills and ability to mentor and (on occasion) delegate to other engineers at various levels of relative seniority.
• A well-established technical design and documentation habit
• Capability to work directly with customers to identify foundational needs and provide solutions.
  
  

Bonus Points(not required): 

• Demonstrated project management expertise / advanced hands-on understanding of project management agility and operational excellence.
• A love for the continuous delivery of value.
• Exposure to backend systems (Node, Python)
• Experience in Game Development or 3D Visualization

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 is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

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.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe 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 without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

We are seeking a highly skilled Software Engineer to play a critical role in evaluating and improving the performance of our autonomous vehicle (AV) technology. This engineer will be responsible for developing and implementing metrics and software tools, primarily using Python, to effectively measure, analyze, and report on the performance of our AV systems. Their work will directly contribute to accelerating the development of safe and reliable autonomous technologies by transforming complex AV data into actionable insights for the organization.

What You'll Be Doing:

• Design AV Performance Analysis Pipelines: Define, design, and implement key pipelines to extract on-road or simulated events and evaluate autonomous vehicle performance (e.g., lane change capability, oscillation/braking metrics, VRU emergence from occlusion).
• Develop Metrics Software and AI-Powered Tools: Leverage strong Python skills to develop frameworks, AI-powered tools, and systems for calculating, aggregating, and visualizing AV performance metrics from large datasets.
• Collaborate Cross-Functionally: Work with systems, software, AI, controls, simulation, and validation teams to understand needs and improve systems like Perception, Prediction, and Planning.
• Ensure Data Quality and Validation: Implement rigorous checks and validation processes to ensure the accuracy and integrity of data used for performance evaluation.
• Document and Share Knowledge: Create clear documentation for metrics and analysis tools, and share best practices with the engineering team.
• Advance Technical Expertise: Proactively evaluate and integrate new technologies and methodologies relevant to autonomous vehicles and software engineering.
  
  

What We're Looking For:

• 5+ years of software engineering experience and a Bachelor's degree in Computer Science or a related field; a Master's degree is a plus.
• Expert-level proficiency in Python and a strong understanding of modern software development principles and best practices.
• Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation and data analysis.
• Proficient with Git and standard version control workflows.
• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts and results to diverse audiences (engineers, product managers, leadership).
• Proven ability to work both independently and effectively as part of a multidisciplinary team.
• Strong attention to detail and a commitment to data quality, accuracy, and rigorous testing.
• Comfortable working in a fast-paced, agile, continuous integration/continuous delivery (CI/CD) environment.
  
  

Bonus Points (not required):

• Experience working with autonomous vehicle sensor data (e.g., LiDAR, camera, radar).
• Familiarity with simulation environments and data generated from AV simulations.
• Experience with data visualization tools (e.g., Looker) for presenting performance metrics.
• Knowledge of statistical analysis and machine learning techniques relevant to performance evaluation.

Success Metrics:

• Successful design and implementation of key autonomous vehicle performance metrics.
• Improvement in the efficiency and effectiveness of AV performance evaluation processes.
• Timely and accurate delivery of data and insights to AV development teams.
• Contribution to the overall advancement and safety of our autonomous vehicle technology.

This is a unique opportunity to make a meaningful impact at Motional by enhancing our data platform and accelerating development speed for our industry-leading autonomous vehicle metrics and capabilities ecosystem. We take pride in having some of the brightest and most dedicated talent in the world on our team. If you're innovative, driven, and eager to tackle challenges, we'd love to have you join us!

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.

Travel Requirements (greater than 20%):

Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

We are seeking a highly skilled Software Engineer to play a critical role in evaluating and improving the performance of our autonomous vehicle (AV) technology. This engineer will be responsible for developing and implementing metrics and software tools, primarily using Python, to effectively measure, analyze, and report on the performance of our AV systems. Their work will directly contribute to accelerating the development of safe and reliable autonomous technologies by transforming complex AV data into actionable insights for the organization.

What You'll Be Doing:

• Design AV Performance Analysis Pipelines: Define, design, and implement key pipelines to extract on-road or simulated events and evaluate autonomous vehicle performance (e.g., lane change capability, oscillation/braking metrics, VRU emergence from occlusion).
• Develop Metrics Software and AI-Powered Tools: Leverage strong Python skills to develop frameworks, AI-powered tools, and systems for calculating, aggregating, and visualizing AV performance metrics from large datasets.
• Collaborate Cross-Functionally: Work with systems, software, AI, controls, simulation, and validation teams to understand needs and improve systems like Perception, Prediction, and Planning.
• Ensure Data Quality and Validation: Implement rigorous checks and validation processes to ensure the accuracy and integrity of data used for performance evaluation.
• Document and Share Knowledge: Create clear documentation for metrics and analysis tools, and share best practices with the engineering team.
• Advance Technical Expertise: Proactively evaluate and integrate new technologies and methodologies relevant to autonomous vehicles and software engineering.
  
  

What We're Looking For:

• 5+ years of software engineering experience and a Bachelor's degree in Computer Science or a related field; a Master's degree is a plus.
• Expert-level proficiency in Python and a strong understanding of modern software development principles and best practices.
• Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation and data analysis.
• Proficient with Git and standard version control workflows.
• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts and results to diverse audiences (engineers, product managers, leadership).
• Proven ability to work both independently and effectively as part of a multidisciplinary team.
• Strong attention to detail and a commitment to data quality, accuracy, and rigorous testing.
• Comfortable working in a fast-paced, agile, continuous integration/continuous delivery (CI/CD) environment.
  
  

Bonus Points (not required):

• Experience working with autonomous vehicle sensor data (e.g., LiDAR, camera, radar).
• Familiarity with simulation environments and data generated from AV simulations.
• Experience with data visualization tools (e.g., Looker) for presenting performance metrics.
• Knowledge of statistical analysis and machine learning techniques relevant to performance evaluation.
  
  

Success Metrics:

• Successful design and implementation of key autonomous vehicle performance metrics.
• Improvement in the efficiency and effectiveness of AV performance evaluation processes.
• Timely and accurate delivery of data and insights to AV development teams.
• Contribution to the overall advancement and safety of our autonomous vehicle technology.

This is a unique opportunity to make a meaningful impact at Motional by enhancing our data platform and accelerating development speed for our industry-leading autonomous vehicle metrics and capabilities ecosystem. We take pride in having some of the brightest and most dedicated talent in the world on our team. If you're innovative, driven, and eager to tackle challenges, we'd love to have you join us!

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.

Travel Requirements (greater than 20%):

Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

Mission Summary:

The Autonomy Subsystems team at Motional is focused on designing and evaluating modules of the autonomy software. We are seeking a talented senior engineer to contribute to evaluation of our machine learning subsystems. Our team performs a variety of evaluations of machine learning models, including offline model eval, evaluation of open and closed-loop re-simulations, and assessment of on-road performance. Our goal is to establish metrics that describe autonomy subsystem performance, evaluate against those metrics to validate performance, and provide meaningful insight to ML developers and teams, working closely alongside them to improve the performance of ML models on the car.

We are looking for a highly-technical systems engineer with experience designing and evaluating safety critical systems and machine learning models. Bring your passion for autonomy, robotics, and machine learning to our team to help build a production-ready system and prepare for our scaled robotaxi service deployment.

Responsibilities:

• Define, prototype, and validate advanced metrics that bring new insights to model performance evaluation for autonomy subsystems (mainly focused on perception, prediction, and planning).
• Assess coverage of existing training and testing, then curate test sets that sufficiently capture Motional’s intended deployment operational design domain, across many axes (agent types, interaction types, map/spatial, etc.).
• Evaluate machine learning model performance against these metrics and tests.
• Assess system-level performance and subsystem contribution to system behavior through large-scale data analysis of on-road and simulation events.
• Define performance requirements for autonomy subsystems, and supporting analyses required to establish these targets.
• Coordinate subsystem-level evaluation with other system-level testing efforts across the systems team in support of the safety case and safety claims.
  
  

Qualifications:

• An engineer who has demonstrated strong cross-functional collaborative skills and is highly self-starting. This is a highly cooperative role across systems, autonomy, infrastructure, and other parts of the organization.
• Proven engineer with 5+ years of experience working on high-tech safety critical systems or robotics, ideally from a systems, robotics, or similar background.
• Master’s degree in relevant fields (systems, robotics, ML, CS, etc.) or Bachelor’s degree plus significant relevant in-field experience.
• Skilled Python developer, familiarity with analyzing the large scale data required to train and test ML models.
• Experience designing unique metrics that capture key aspects of system behavior and are used to enhance model development.
  
  

Bonus Skills:

• Experience training machine learning models, familiarity with state-of-the-art ML model architectures.
• Deep experience with a specific aspect of machine learning for autonomous robotics (perception, prediction, or planning).
• Knowledge of C++, especially applied to safety critical systems.
• Experience with systems verification and validation techniques
• Experience with regression testing updates to already-deployed software in a safety-critical environment.
• Experience with automotive standards (E.g: ISO 12207, ISO 26262, ISO 21448)
• Experience with software quality management and assurance activities (E.g: IATF 16949, ISO 9001)
• Thorough understanding of robotics systems including sensors, actuators, mechatronics and software systems
• Work in cross collaboration teams to address problems and find solutions
  
  

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.

Travel Requirements (greater than 20%):
Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe 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 without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

Mission Summary:

Motional is seeking a Staff Front End Engineer expert for its Web Visualization Tooling team.  This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improve the performance and adaptability of our autonomous vehicle (AV) system.

What you'll be doing:

• Drive cross-team standards and best practices for web development
• Own cross team collaboration, ensuring deliveries are made on time and effectively
• Architect and scale a modern frontend ecosystem using React, TypeScript, and Vue.
• Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to align tooling with real-world workflows
• Build mission-critical UI systems used by a variety of internal customers.
• Design initiative experiences for complex, data-heavy workflows.
• Drive best practices around performance, scalability and maintainability
• Ship quickly and iterate in a product driven environment.
  
  

What we're looking for:

• Desire to design and build user-facing visual applications, and a passion for good UX.
• Strong proficiency in React, Typescript and modern frontend architecture
• Proficiency in Vue
• Strong product sense with a focus on UX and usability.
• Ability to work with high ownership and autonomy.
• Ability to work autonomously and independently, and to drive development initiatives with little oversight. High aptitude for learning and organization skills.
• Great interpersonal skills and ability to mentor and (on occasion) delegate to other engineers at various levels of relative seniority.
• A well-established technical design and documentation habit
• Capability to work directly with customers to identify foundational needs and provide solutions.
  
  

Bonus Points(not required): 

• Demonstrated project management expertise / advanced hands-on understanding of project management agility and operational excellence.
• A love for the continuous delivery of value.
• Exposure to backend systems (Node, Python)
• Experience in Game Development or 3D Visualization

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 is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

We are seeking a highly skilled Software Engineer to play a critical role in evaluating and improving the performance of our autonomous vehicle (AV) technology. This engineer will be responsible for developing and implementing metrics and software tools, primarily using Python, to effectively measure, analyze, and report on the performance of our AV systems. Their work will directly contribute to accelerating the development of safe and reliable autonomous technologies by transforming complex AV data into actionable insights for the organization.

What You'll Be Doing:

• Design AV Performance Analysis Pipelines: Define, design, and implement key pipelines to extract on-road or simulated events and evaluate autonomous vehicle performance (e.g., lane change capability, oscillation/braking metrics, VRU emergence from occlusion).
• Develop Metrics Software and AI-Powered Tools: Leverage strong Python skills to develop frameworks, AI-powered tools, and systems for calculating, aggregating, and visualizing AV performance metrics from large datasets.
• Collaborate Cross-Functionally: Work with systems, software, AI, controls, simulation, and validation teams to understand needs and improve systems like Perception, Prediction, and Planning.
• Ensure Data Quality and Validation: Implement rigorous checks and validation processes to ensure the accuracy and integrity of data used for performance evaluation.
• Document and Share Knowledge: Create clear documentation for metrics and analysis tools, and share best practices with the engineering team.
• Advance Technical Expertise: Proactively evaluate and integrate new technologies and methodologies relevant to autonomous vehicles and software engineering.
  
  

What We're Looking For:

• 5+ years of software engineering experience and a Bachelor's degree in Computer Science or a related field; a Master's degree is a plus.
• Expert-level proficiency in Python and a strong understanding of modern software development principles and best practices.
• Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation and data analysis.
• Proficient with Git and standard version control workflows.
• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts and results to diverse audiences (engineers, product managers, leadership).
• Proven ability to work both independently and effectively as part of a multidisciplinary team.
• Strong attention to detail and a commitment to data quality, accuracy, and rigorous testing.
• Comfortable working in a fast-paced, agile, continuous integration/continuous delivery (CI/CD) environment.
  
  

Bonus Points (not required):

• Experience working with autonomous vehicle sensor data (e.g., LiDAR, camera, radar).
• Familiarity with simulation environments and data generated from AV simulations.
• Experience with data visualization tools (e.g., Looker) for presenting performance metrics.
• Knowledge of statistical analysis and machine learning techniques relevant to performance evaluation.

Success Metrics:

• Successful design and implementation of key autonomous vehicle performance metrics.
• Improvement in the efficiency and effectiveness of AV performance evaluation processes.
• Timely and accurate delivery of data and insights to AV development teams.
• Contribution to the overall advancement and safety of our autonomous vehicle technology.

This is a unique opportunity to make a meaningful impact at Motional by enhancing our data platform and accelerating development speed for our industry-leading autonomous vehicle metrics and capabilities ecosystem. We take pride in having some of the brightest and most dedicated talent in the world on our team. If you're innovative, driven, and eager to tackle challenges, we'd love to have you join us!

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.

Travel Requirements (greater than 20%):

Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

Motional is a leading autonomous driving company on a mission to make driverless vehicles a safe, reliable, and accessible reality. Backed by Hyundai Motor Group, Motional is at the forefront of the physical AI revolution. Motional isn’t just building first-of-its-kind technology; we are transforming transportation to create safer streets and more sustainable mobility options.

The Systems Readiness and Performance team is the crucial bridge between software development and real-world deployment. We are responsible for driving system design, for verifying and validating the autonomy stack, and for defining, measuring, and validating system performance targets. We work closely with stakeholders in autonomy, infrastructure, and operations to build the definitive safety case for the commercial launch of our fully driverless IONIQ 5 robotaxis in Las Vegas later this year.

We are seeking a highly skilled Software Engineer to play a critical role in evaluating and improving the performance of our autonomous vehicle (AV) technology. This engineer will be responsible for developing and implementing metrics and software tools, primarily using Python, to effectively measure, analyze, and report on the performance of our AV systems. Their work will directly contribute to accelerating the development of safe and reliable autonomous technologies by transforming complex AV data into actionable insights for the organization.

What You'll Be Doing:

• Design AV Performance Analysis Pipelines: Define, design, and implement key pipelines to extract on-road or simulated events and evaluate autonomous vehicle performance (e.g., lane change capability, oscillation/braking metrics, VRU emergence from occlusion).
• Develop Metrics Software and AI-Powered Tools: Leverage strong Python skills to develop frameworks, AI-powered tools, and systems for calculating, aggregating, and visualizing AV performance metrics from large datasets.
• Collaborate Cross-Functionally: Work with systems, software, AI, controls, simulation, and validation teams to understand needs and improve systems like Perception, Prediction, and Planning.
• Ensure Data Quality and Validation: Implement rigorous checks and validation processes to ensure the accuracy and integrity of data used for performance evaluation.
• Document and Share Knowledge: Create clear documentation for metrics and analysis tools, and share best practices with the engineering team.
• Advance Technical Expertise: Proactively evaluate and integrate new technologies and methodologies relevant to autonomous vehicles and software engineering.
  
  

What We're Looking For:

• 5+ years of software engineering experience and a Bachelor's degree in Computer Science or a related field; a Master's degree is a plus.
• Expert-level proficiency in Python and a strong understanding of modern software development principles and best practices.
• Strong analytical and problem-solving skills, particularly in the context of complex system performance evaluation and data analysis.
• Proficient with Git and standard version control workflows.
• Excellent communication and collaboration skills, with the ability to effectively communicate technical concepts and results to diverse audiences (engineers, product managers, leadership).
• Proven ability to work both independently and effectively as part of a multidisciplinary team.
• Strong attention to detail and a commitment to data quality, accuracy, and rigorous testing.
• Comfortable working in a fast-paced, agile, continuous integration/continuous delivery (CI/CD) environment.
  
  

Bonus Points (not required):

• Experience working with autonomous vehicle sensor data (e.g., LiDAR, camera, radar).
• Familiarity with simulation environments and data generated from AV simulations.
• Experience with data visualization tools (e.g., Looker) for presenting performance metrics.
• Knowledge of statistical analysis and machine learning techniques relevant to performance evaluation.

Success Metrics:

• Successful design and implementation of key autonomous vehicle performance metrics.
• Improvement in the efficiency and effectiveness of AV performance evaluation processes.
• Timely and accurate delivery of data and insights to AV development teams.
• Contribution to the overall advancement and safety of our autonomous vehicle technology.

This is a unique opportunity to make a meaningful impact at Motional by enhancing our data platform and accelerating development speed for our industry-leading autonomous vehicle metrics and capabilities ecosystem. We take pride in having some of the brightest and most dedicated talent in the world on our team. If you're innovative, driven, and eager to tackle challenges, we'd love to have you join us!

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.

Travel Requirements (greater than 20%):

Expected to travel for 1-2 weeks each quarter visiting all of our testing sites - mostly to LV, but also domestically as needed for the business.

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. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

Mission Summary:

Reporting to the Senior Business Development Manager the Strategic Partner Lead, Customer Success will be responsible for identifying, building, and nurturing strategic partnerships that drive growth and expand opportunities with key commercial partners. 

This is a pivotal time to join Motional. We are transitioning from development to deployment, launching our commercial driverless service in Las Vegas in 2026. In collaboration with a major ride-hail partner, we are setting the stage to scale this technology to dozens of cities across the U.S. and internationally. This role requires a leader with a proven track record in forging successful alliances, negotiating complex agreements, and managing relationships with key stakeholders. You will serve as the "Voice of the Customer," owning the relationship at all levels of the organization, playing a critical role in shaping our commercial strategy and achieving our long-term objectives, ensuring our commercial operations translate into scalable, revenue-generating reality. 

This role will be expected to travel up to 40% of the time depending on the business purpose and partnership deliverables.

What you'll be doing:

• Own the Partner Relationship: Serve as the primary commercial owner for critical accounts, navigating complex stakeholder maps to connect internal leads with their external counterparts. You will drive account health, retention, and efficiency by ensuring the right people are connected at the right time.
• Drive Cross-Functional Alignment: Act as the operational bridge between Commercial and technical execution teams (Product, Ops, TPM). You will translate high-level commercial milestones into clear directives, ensuring workstreams converge on time for successful deployments.
• Lead Strategic Collaborations: Establish the partnership's rhythm of business, including Quarterly Business Reviews (QBRs), Steering Committees, and executive briefings. You will lead internal alignment to ensure high-stakes partner events and demos are executed flawlessly.
• Define Success & Track KPIs: Define what winning looks like for both Motional and our partners. You will track and report on key performance indicators across teams to ensure we are meeting contractual obligations and commercial goals.
• Support Market Expansion: Lead the rollout strategy for new launch markets, coordinating logistics between Operations, Strategy, technical teams and external partners. You will drive the readiness efforts required to move from pilot zones to full commercial scale.
• Create Data-Driven Feedback Loops: Translate partner insights—such as pickup/drop-off friction—into actionable engineering requests. You will close the loop between commercial reality and technical roadmaps to optimize the end-to-end passenger experience
  
  

What we're looking for:

• Bachelor's degree in Business, Engineering, or equivalent field, or commensurate professional experience.
• 7+ years relevant professional experience in a similar role, experience working with autonomous vehicles, ride-hail, robotics or mobility industries.
• Cross-Functional Leadership: You have a proven ability to coordinate complex projects across technical and non-technical teams. You can translate commercial needs into clear directives for Product and Operations.
• Executive Presence: You possess superb communication skills and can command a room. You are experienced in leading executive presentations, QBRs, and high-visibility partner visits with polish and professionalism.
• Strategic & Operational Balance: You can set the long-term vision with a partner while also sweating the details of a short term project. You understand how to align daily execution with multi-year commercial objectives.
• Analytical & Influential: You can use data to build a compelling point of view that influences internal stakeholders. You know how to advocate for the partner’s needs to shape our long-term product strategy.
• Soft skills that earn the confidence of leaders and peers, including empathy, organization, clear communication, influencing without authority, low ego, and the ability to build trust.
  
  

Bonus Points(not required):

• MBA or equivalent advanced business degree.
• Launch Experience: Experience coordinating the commercial side of a product launch in a physical market.
• Commercial Fluency: Experience supporting business development efforts, contract renewals, or opportunities.
  
  

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

Mission Summary:

As a Technical Lead Manager at Motional, you'll lead a team responsible for the development and delivery of core trajectory planning algorithms via numerical optimization for autonomous vehicles. In this role, you will be at the forefront of shaping the motion planning and control systems that enable our fleet to navigate complex environments safely, efficiently, and comfortably. As a key leader, you will drive the development and continuous performance improvements of cutting-edge trajectory generation algorithms, collaborate with cross-functional teams (Planning, Perception, Prediction, Localization, ML Products, and Systems Engineering), and mentor a talented group of highly skilled engineers to deliver state-of-the-art solutions. 

If you are passionate about autonomous driving and being part of our commercial launch this year, thrive on solving challenging real-world problems, and eager to make a significant impact in a rapidly evolving field, we want to hear from you!

What you'll do:

• Lead and scale a high-impact trajectory planning team, defining its technical vision, execution strategy, and long-term organizational role within the Motion organization.
• Drive commercial launch readiness for trajectory planning by delivering on-road driving behavior improvements (safety, comfort, and assertiveness) across the fleet through feature expansion, continuous performance improvements, and innovation through state-of-the art methods.
• Apply a rigorous, metrics-driven framework to quantify and improve on-road performance. Champion leveraging existing training and evaluation pipelines to ensure scalable, production-ready delivery.
• Manage the computational efficiency and real-time performance of trajectory generation algorithms, ensuring latency budget compliance.
• Lead the rapid triage and root-cause analysis (RCA) of critical fleet incidents, translating real-world edge cases into immediate algorithmic refinements and validation sets.
• Oversee the successful execution of complex, multi-team initiatives, ensuring technical alignment from design through deployment while maintaining a rigorous standard for testing and validation to meet the high safety bars required for our commercial launch.
• Coordinate with peer leads to provide technical leadership, making consequential decisions on architectural direction, strategic investments, tactical execution, and technical debt reduction.Ensure technical excellence through rigorous design and code reviews while actively facilitating the professional growth and mentorship of your engineering team. Set and drive ambitious goals that challenge the team to deliver industry-leading trajectory planning solutions.
• Define and negotiate quarterly and annual technical roadmaps aligned with company-level autonomy milestones in coordinate with project managers and execute plans on schedule.
  
  

What we're looking for:

• Proven Engineering Leadership: 2+ years of experience managing high-performing development teams, with a demonstrable track record of inspiring, mentoring, and coaching engineers and driving measurable productivity gains.
• Ship-to-Production Mindset: Experience leading the delivery of production-quality algorithms in a high-stakes environment (Autonomous Vehicles, Robotics, or Aerospace). You know what it takes to move from a prototype to a commercially viable product.
• Strategic Vision: Ability to look beyond the immediate deliverables to define and defend a balanced technical roadmap that balances long-term architectural health with the urgent needs of a 2026 commercial launch.
• Technical Domain Expertise: Deep theoretical and practical expertise in numerical optimization and optimal control. You should be highly proficient in areas such as Model Predictive Control, nonlinear programming, and convex optimization applied to real-time trajectory generation.
• Advanced Motion Planning: Significant experience solving motion planning problems under uncertainty, including interaction-aware planning with dynamic agents and complex environmental constraints. Experience with Machine Learning based approaches is a significant plus.
• Full-Stack Robotics Context: Strong intuition for the entire robotics stack. You understand how upstream (Perception, Prediction) and downstream (Control, Actuation) systems impact trajectory feasibility and fleet safety.
• Production-Grade Software Development: Expertise in Modern C++ development within a Linux environment, with a focus on writing high-performance, real-time, and safety-critical code.
• Tooling Proficiency: Fluency in Python for rapid prototyping, data analysis, and visualization. Experience applying AI-augmented development workflows to large-scale Modern C++ codebases (e.g., agentic tools for multi-file refactoring, automated test generation, semantic code navigation, and code review acceleration) is strongly preferred. Experience with SQL or big-data frameworks for fleet-scale performance analysis is a significant plus.
• Influence & Clarity: Exceptional communication skills, with the ability to translate complex mathematical concepts into actionable plans for cross-functional stakeholders and executive leadership.
• Educational Foundation: Master’s or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related quantitative field.
  
  

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 Technical Lead Manager at Motional, you'll lead a team responsible for the development and delivery of core trajectory planning algorithms via numerical optimization for autonomous vehicles. In this role, you will be at the forefront of shaping the motion planning and control systems that enable our fleet to navigate complex environments safely, efficiently, and comfortably. As a key leader, you will drive the development and continuous performance improvements of cutting-edge trajectory generation algorithms, collaborate with cross-functional teams (Planning, Perception, Prediction, Localization, ML Products, and Systems Engineering), and mentor a talented group of highly skilled engineers to deliver state-of-the-art solutions. 

If you are passionate about autonomous driving and being part of our commercial launch this year, thrive on solving challenging real-world problems, and eager to make a significant impact in a rapidly evolving field, we want to hear from you!

What you'll do:

• Lead and scale a high-impact trajectory planning team, defining its technical vision, execution strategy, and long-term organizational role within the Motion organization.
• Drive commercial launch readiness for trajectory planning by delivering on-road driving behavior improvements (safety, comfort, and assertiveness) across the fleet through feature expansion, continuous performance improvements, and innovation through state-of-the art methods.
• Apply a rigorous, metrics-driven framework to quantify and improve on-road performance. Champion leveraging existing training and evaluation pipelines to ensure scalable, production-ready delivery.
• Manage the computational efficiency and real-time performance of trajectory generation algorithms, ensuring latency budget compliance.
• Lead the rapid triage and root-cause analysis (RCA) of critical fleet incidents, translating real-world edge cases into immediate algorithmic refinements and validation sets.
• Oversee the successful execution of complex, multi-team initiatives, ensuring technical alignment from design through deployment while maintaining a rigorous standard for testing and validation to meet the high safety bars required for our commercial launch.
• Coordinate with peer leads to provide technical leadership, making consequential decisions on architectural direction, strategic investments, tactical execution, and technical debt reduction.Ensure technical excellence through rigorous design and code reviews while actively facilitating the professional growth and mentorship of your engineering team. Set and drive ambitious goals that challenge the team to deliver industry-leading trajectory planning solutions.
• Define and negotiate quarterly and annual technical roadmaps aligned with company-level autonomy milestones in coordinate with project managers and execute plans on schedule.
  
  

What we're looking for:

• Proven Engineering Leadership: 2+ years of experience managing high-performing development teams, with a demonstrable track record of inspiring, mentoring, and coaching engineers and driving measurable productivity gains.
• Ship-to-Production Mindset: Experience leading the delivery of production-quality algorithms in a high-stakes environment (Autonomous Vehicles, Robotics, or Aerospace). You know what it takes to move from a prototype to a commercially viable product.
• Strategic Vision: Ability to look beyond the immediate deliverables to define and defend a balanced technical roadmap that balances long-term architectural health with the urgent needs of a 2026 commercial launch.
• Technical Domain Expertise: Deep theoretical and practical expertise in numerical optimization and optimal control. You should be highly proficient in areas such as Model Predictive Control, nonlinear programming, and convex optimization applied to real-time trajectory generation.
• Advanced Motion Planning: Significant experience solving motion planning problems under uncertainty, including interaction-aware planning with dynamic agents and complex environmental constraints. Experience with Machine Learning based approaches is a significant plus.
• Full-Stack Robotics Context: Strong intuition for the entire robotics stack. You understand how upstream (Perception, Prediction) and downstream (Control, Actuation) systems impact trajectory feasibility and fleet safety.
• Production-Grade Software Development: Expertise in Modern C++ development within a Linux environment, with a focus on writing high-performance, real-time, and safety-critical code.
• Tooling Proficiency: Fluency in Python for rapid prototyping, data analysis, and visualization. Experience applying AI-augmented development workflows to large-scale Modern C++ codebases (e.g., agentic tools for multi-file refactoring, automated test generation, semantic code navigation, and code review acceleration) is strongly preferred. Experience with SQL or big-data frameworks for fleet-scale performance analysis is a significant plus.
• Influence & Clarity: Exceptional communication skills, with the ability to translate complex mathematical concepts into actionable plans for cross-functional stakeholders and executive leadership.
• Educational Foundation: Master’s or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related quantitative field.
  
  

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.

Mission Summary:

As a Technical Lead Manager at Motional, you'll lead a team responsible for the development and delivery of core trajectory planning algorithms via numerical optimization for autonomous vehicles. In this role, you will be at the forefront of shaping the motion planning and control systems that enable our fleet to navigate complex environments safely, efficiently, and comfortably. As a key leader, you will drive the development and continuous performance improvements of cutting-edge trajectory generation algorithms, collaborate with cross-functional teams (Planning, Perception, Prediction, Localization, ML Products, and Systems Engineering), and mentor a talented group of highly skilled engineers to deliver state-of-the-art solutions. 

If you are passionate about autonomous driving and being part of our commercial launch this year, thrive on solving challenging real-world problems, and eager to make a significant impact in a rapidly evolving field, we want to hear from you!

What you'll do:

• Lead and scale a high-impact trajectory planning team, defining its technical vision, execution strategy, and long-term organizational role within the Motion organization.
• Drive commercial launch readiness for trajectory planning by delivering on-road driving behavior improvements (safety, comfort, and assertiveness) across the fleet through feature expansion, continuous performance improvements, and innovation through state-of-the art methods.
• Apply a rigorous, metrics-driven framework to quantify and improve on-road performance. Champion leveraging existing training and evaluation pipelines to ensure scalable, production-ready delivery.
• Manage the computational efficiency and real-time performance of trajectory generation algorithms, ensuring latency budget compliance.
• Lead the rapid triage and root-cause analysis (RCA) of critical fleet incidents, translating real-world edge cases into immediate algorithmic refinements and validation sets.
• Oversee the successful execution of complex, multi-team initiatives, ensuring technical alignment from design through deployment while maintaining a rigorous standard for testing and validation to meet the high safety bars required for our commercial launch.
• Coordinate with peer leads to provide technical leadership, making consequential decisions on architectural direction, strategic investments, tactical execution, and technical debt reduction.Ensure technical excellence through rigorous design and code reviews while actively facilitating the professional growth and mentorship of your engineering team. Set and drive ambitious goals that challenge the team to deliver industry-leading trajectory planning solutions.
• Define and negotiate quarterly and annual technical roadmaps aligned with company-level autonomy milestones in coordinate with project managers and execute plans on schedule.
  
  

What we're looking for:

• Proven Engineering Leadership: 2+ years of experience managing high-performing development teams, with a demonstrable track record of inspiring, mentoring, and coaching engineers and driving measurable productivity gains.
• Ship-to-Production Mindset: Experience leading the delivery of production-quality algorithms in a high-stakes environment (Autonomous Vehicles, Robotics, or Aerospace). You know what it takes to move from a prototype to a commercially viable product.
• Strategic Vision: Ability to look beyond the immediate deliverables to define and defend a balanced technical roadmap that balances long-term architectural health with the urgent needs of a 2026 commercial launch.
• Technical Domain Expertise: Deep theoretical and practical expertise in numerical optimization and optimal control. You should be highly proficient in areas such as Model Predictive Control, nonlinear programming, and convex optimization applied to real-time trajectory generation.
• Advanced Motion Planning: Significant experience solving motion planning problems under uncertainty, including interaction-aware planning with dynamic agents and complex environmental constraints. Experience with Machine Learning based approaches is a significant plus.
• Full-Stack Robotics Context: Strong intuition for the entire robotics stack. You understand how upstream (Perception, Prediction) and downstream (Control, Actuation) systems impact trajectory feasibility and fleet safety.
• Production-Grade Software Development: Expertise in Modern C++ development within a Linux environment, with a focus on writing high-performance, real-time, and safety-critical code.
• Tooling Proficiency: Fluency in Python for rapid prototyping, data analysis, and visualization. Experience applying AI-augmented development workflows to large-scale Modern C++ codebases (e.g., agentic tools for multi-file refactoring, automated test generation, semantic code navigation, and code review acceleration) is strongly preferred. Experience with SQL or big-data frameworks for fleet-scale performance analysis is a significant plus.
• Influence & Clarity: Exceptional communication skills, with the ability to translate complex mathematical concepts into actionable plans for cross-functional stakeholders and executive leadership.
• Educational Foundation: Master’s or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related quantitative field.
  
  

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:

We are looking for a Senior Software Engineer to develop and deliver automated workflows, intelligent tooling and insightful analytics that enables our autonomy stack to scale. You will play a pivotal role in transforming massive amounts of data into actionable engineering insights, ensuring our software releases are robust, validated, and ready for the road.

What you'll be doing:

• Develop Intelligent Tooling: You will design and implement sophisticated automation to categorize and explain complex system behaviors by leveraging advanced data modeling to accelerate solutions.
• Drive Analytics: You’ll lead the creation of high-impact performance visualization tools that translate raw metrics into clear, actionable insights regarding on-road performance.
• Streamline Release Engineering: Your expertise will help the team evolve our release processes, moving toward a highly automated deployment framework that maintains quality while improving efficiency
• Advance Simulation Capabilities: You’ll have the opportunity to enhance our virtual testing ecosystems, ensuring our simulation suites provide the high fidelity feedback necessary to properly understand the release.
• Collaborate at Scale: Work within a large, multi-disciplinary codebase to ensure seamless integration between planning, motion, and controls teams.
  
  

What we're looking for:

• Extensive experience building production-grade applications, tools, and pipelines using Python.
• Comfortable navigating and contributing to large, complex codebases where modularity and documentation are key.
• Proven track record of delivering software in a production environment, including familiarity with CI/CD, version control at scale, and rigorous release cycles.
• Curious about data and possess the ability to extract meaningful patterns from noisy, high-dimensional datasets.
• Passionate about a driverless future and understand the high stakes of deploying software that interacts with the physical world.
  
  

Bonus Points(not required): 

• Experience with C++ in a Linux environment.
• Familiarity with Machine Learning frameworks or Large Language Model (LLM) integration.
• Background in robotics middleware (ROS, DDS) or autonomous systems.
  
  

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:

We are looking for a Senior Software Engineer to develop and deliver automated workflows, intelligent tooling and insightful analytics that enables our autonomy stack to scale. You will play a pivotal role in transforming massive amounts of data into actionable engineering insights, ensuring our software releases are robust, validated, and ready for the road.

What you'll be doing:

• Develop Intelligent Tooling: You will design and implement sophisticated automation to categorize and explain complex system behaviors by leveraging advanced data modeling to accelerate solutions.
• Drive Analytics: You’ll lead the creation of high-impact performance visualization tools that translate raw metrics into clear, actionable insights regarding on-road performance.
• Streamline Release Engineering: Your expertise will help the team evolve our release processes, moving toward a highly automated deployment framework that maintains quality while improving efficiency
• Advance Simulation Capabilities: You’ll have the opportunity to enhance our virtual testing ecosystems, ensuring our simulation suites provide the high fidelity feedback necessary to properly understand the release.
• Collaborate at Scale: Work within a large, multi-disciplinary codebase to ensure seamless integration between planning, motion, and controls teams.
  
  

What we're looking for:

• Extensive experience building production-grade applications, tools, and pipelines using Python.
• Comfortable navigating and contributing to large, complex codebases where modularity and documentation are key.
• Proven track record of delivering software in a production environment, including familiarity with CI/CD, version control at scale, and rigorous release cycles.
• Curious about data and possess the ability to extract meaningful patterns from noisy, high-dimensional datasets.
• Passionate about a driverless future and understand the high stakes of deploying software that interacts with the physical world.
  
  

Bonus Points(not required): 

• Experience with C++ in a Linux environment.
• Familiarity with Machine Learning frameworks or Large Language Model (LLM) integration.
• Background in robotics middleware (ROS, DDS) or autonomous systems.
  
  

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 Technical Lead Manager at Motional, you'll lead a team responsible for the development and delivery of core trajectory planning algorithms via numerical optimization for autonomous vehicles. In this role, you will be at the forefront of shaping the motion planning and control systems that enable our fleet to navigate complex environments safely, efficiently, and comfortably. As a key leader, you will drive the development and continuous performance improvements of cutting-edge trajectory generation algorithms, collaborate with cross-functional teams (Planning, Perception, Prediction, Localization, ML Products, and Systems Engineering), and mentor a talented group of highly skilled engineers to deliver state-of-the-art solutions. 

If you are passionate about autonomous driving and being part of our commercial launch this year, thrive on solving challenging real-world problems, and eager to make a significant impact in a rapidly evolving field, we want to hear from you!

What you'll do:

• Lead and scale a high-impact trajectory planning team, defining its technical vision, execution strategy, and long-term organizational role within the Motion organization.
• Drive commercial launch readiness for trajectory planning by delivering on-road driving behavior improvements (safety, comfort, and assertiveness) across the fleet through feature expansion, continuous performance improvements, and innovation through state-of-the art methods.
• Apply a rigorous, metrics-driven framework to quantify and improve on-road performance. Champion leveraging existing training and evaluation pipelines to ensure scalable, production-ready delivery.
• Manage the computational efficiency and real-time performance of trajectory generation algorithms, ensuring latency budget compliance.
• Lead the rapid triage and root-cause analysis (RCA) of critical fleet incidents, translating real-world edge cases into immediate algorithmic refinements and validation sets.
• Oversee the successful execution of complex, multi-team initiatives, ensuring technical alignment from design through deployment while maintaining a rigorous standard for testing and validation to meet the high safety bars required for our commercial launch.
• Coordinate with peer leads to provide technical leadership, making consequential decisions on architectural direction, strategic investments, tactical execution, and technical debt reduction.Ensure technical excellence through rigorous design and code reviews while actively facilitating the professional growth and mentorship of your engineering team. Set and drive ambitious goals that challenge the team to deliver industry-leading trajectory planning solutions.
• Define and negotiate quarterly and annual technical roadmaps aligned with company-level autonomy milestones in coordinate with project managers and execute plans on schedule.
  
  

What we're looking for:

• Proven Engineering Leadership: 2+ years of experience managing high-performing development teams, with a demonstrable track record of inspiring, mentoring, and coaching engineers and driving measurable productivity gains.
• Ship-to-Production Mindset: Experience leading the delivery of production-quality algorithms in a high-stakes environment (Autonomous Vehicles, Robotics, or Aerospace). You know what it takes to move from a prototype to a commercially viable product.
• Strategic Vision: Ability to look beyond the immediate deliverables to define and defend a balanced technical roadmap that balances long-term architectural health with the urgent needs of a 2026 commercial launch.
• Technical Domain Expertise: Deep theoretical and practical expertise in numerical optimization and optimal control. You should be highly proficient in areas such as Model Predictive Control, nonlinear programming, and convex optimization applied to real-time trajectory generation.
• Advanced Motion Planning: Significant experience solving motion planning problems under uncertainty, including interaction-aware planning with dynamic agents and complex environmental constraints. Experience with Machine Learning based approaches is a significant plus.
• Full-Stack Robotics Context: Strong intuition for the entire robotics stack. You understand how upstream (Perception, Prediction) and downstream (Control, Actuation) systems impact trajectory feasibility and fleet safety.
• Production-Grade Software Development: Expertise in Modern C++ development within a Linux environment, with a focus on writing high-performance, real-time, and safety-critical code.
• Tooling Proficiency: Fluency in Python for rapid prototyping, data analysis, and visualization. Experience applying AI-augmented development workflows to large-scale Modern C++ codebases (e.g., agentic tools for multi-file refactoring, automated test generation, semantic code navigation, and code review acceleration) is strongly preferred. Experience with SQL or big-data frameworks for fleet-scale performance analysis is a significant plus.
• Influence & Clarity: Exceptional communication skills, with the ability to translate complex mathematical concepts into actionable plans for cross-functional stakeholders and executive leadership.
• Educational Foundation: Master’s or PhD in Robotics, Computer Science, Electrical/Mechanical Engineering, or a related quantitative field.
  
  

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 is seeking a Senior Full Stack Engineer expert for its Web Visualization Tooling team.  This role will directly contribute through the creation of critical web tooling and visualization that allows us to improve our feedback loops for machine learning (ML) engineers and improving the performance and adaptability of our autonomous vehicle (AV) system.

Role Responsibilities:

• Own and expand backend implementation and architecture of our visualization tooling suite (e.g., data mining quality assurance, operations and log ingestion, annotation pipelines, telemetry viewers).
• Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to align tooling with real-world workflows
• Support scalable, performance APIs and services for visual development, debugging, and annotation systems.
• Help mature internal standards, observability, and deployment processes for our backend stack
• Maintain and mature the team’s CI/CD infrastructure and process.

Qualifications (required):

• Desire to design and build user-facing visual applications, and a passion for good UX.
• Strong proficiency in backend development with NodeJS and Python.
• Solid understanding and practical experience with AWS CDK in TypeScript.
• Ability to own and expand backend implementation and architecture of visualization tooling suite.
• Proven ability to collaborate effectively with cross-functional teams in diverse and highly technical domains of expertise.
• Experience in supporting scalable, high-performance APIs and services for visual development, debugging, and annotation systems.
• Ability to help mature internal standards, observability, and deployment processes for backend stack.
• Experience in maintaining and maturing CI/CD infrastructure and processes.
• Ability to work autonomously and independently, and to drive development initiatives with little oversight. High aptitude for learning and organization skills.
• Great interpersonal skills and ability to mentor and (on occasion) delegate to other engineers at various levels of relative seniority.
• A well-established technical design and documentation habit

Preferred:

• Experience with full-stack and front-end development using NextJS and React.
• Demonstrated project management expertise / advanced hands-on understanding of project management agility and operational excellence.
• A love for the continuous delivery of value.

Nice to have:

• Knowledge of and experience with Golang
• UI/UX and product design experience.
• 3D Math and Linear Algebra fundamentals.
  
  

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:

Reporting to the Senior Business Development Manager the Strategic Partner Lead, Customer Success will be responsible for identifying, building, and nurturing strategic partnerships that drive growth and expand opportunities with key commercial partners. 

This is a pivotal time to join Motional. We are transitioning from development to deployment, launching our commercial driverless service in Las Vegas in 2026. In collaboration with a major ride-hail partner, we are setting the stage to scale this technology to dozens of cities across the U.S. and internationally. This role requires a leader with a proven track record in forging successful alliances, negotiating complex agreements, and managing relationships with key stakeholders. You will serve as the "Voice of the Customer," owning the relationship at all levels of the organization, playing a critical role in shaping our commercial strategy and achieving our long-term objectives, ensuring our commercial operations translate into scalable, revenue-generating reality. 

This role will be expected to travel up to 40% of the time depending on the business purpose and partnership deliverables.

What you'll be doing:

• Own the Partner Relationship: Serve as the primary commercial owner for critical accounts, navigating complex stakeholder maps to connect internal leads with their external counterparts. You will drive account health, retention, and efficiency by ensuring the right people are connected at the right time.
• Drive Cross-Functional Alignment: Act as the operational bridge between Commercial and technical execution teams (Product, Ops, TPM). You will translate high-level commercial milestones into clear directives, ensuring workstreams converge on time for successful deployments.
• Lead Strategic Collaborations: Establish the partnership's rhythm of business, including Quarterly Business Reviews (QBRs), Steering Committees, and executive briefings. You will lead internal alignment to ensure high-stakes partner events and demos are executed flawlessly.
• Define Success & Track KPIs: Define what winning looks like for both Motional and our partners. You will track and report on key performance indicators across teams to ensure we are meeting contractual obligations and commercial goals.
• Support Market Expansion: Lead the rollout strategy for new launch markets, coordinating logistics between Operations, Strategy, technical teams and external partners. You will drive the readiness efforts required to move from pilot zones to full commercial scale.
• Create Data-Driven Feedback Loops: Translate partner insights—such as pickup/drop-off friction—into actionable engineering requests. You will close the loop between commercial reality and technical roadmaps to optimize the end-to-end passenger experience
  
  

What we're looking for:

• Bachelor's degree in Business, Engineering, or equivalent field, or commensurate professional experience.
• 7+ years relevant professional experience in a similar role, experience working with autonomous vehicles, ride-hail, robotics or mobility industries.
• Cross-Functional Leadership: You have a proven ability to coordinate complex projects across technical and non-technical teams. You can translate commercial needs into clear directives for Product and Operations.
• Executive Presence: You possess superb communication skills and can command a room. You are experienced in leading executive presentations, QBRs, and high-visibility partner visits with polish and professionalism.
• Strategic & Operational Balance: You can set the long-term vision with a partner while also sweating the details of a short term project. You understand how to align daily execution with multi-year commercial objectives.
• Analytical & Influential: You can use data to build a compelling point of view that influences internal stakeholders. You know how to advocate for the partner’s needs to shape our long-term product strategy.
• Soft skills that earn the confidence of leaders and peers, including empathy, organization, clear communication, influencing without authority, low ego, and the ability to build trust.
  
  

Bonus Points(not required):

• MBA or equivalent advanced business degree.
• Launch Experience: Experience coordinating the commercial side of a product launch in a physical market.
• Commercial Fluency: Experience supporting business development efforts, contract renewals, or opportunities.
  
  

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

Mission Summary:

We are looking for a Senior Software Engineer to develop and deliver automated workflows, intelligent tooling and insightful analytics that enables our autonomy stack to scale. You will play a pivotal role in transforming massive amounts of data into actionable engineering insights, ensuring our software releases are robust, validated, and ready for the road.

What you'll be doing:

• Develop Intelligent Tooling: You will design and implement sophisticated automation to categorize and explain complex system behaviors by leveraging advanced data modeling to accelerate solutions.
• Drive Analytics: You’ll lead the creation of high-impact performance visualization tools that translate raw metrics into clear, actionable insights regarding on-road performance.
• Streamline Release Engineering: Your expertise will help the team evolve our release processes, moving toward a highly automated deployment framework that maintains quality while improving efficiency
• Advance Simulation Capabilities: You’ll have the opportunity to enhance our virtual testing ecosystems, ensuring our simulation suites provide the high fidelity feedback necessary to properly understand the release.
• Collaborate at Scale: Work within a large, multi-disciplinary codebase to ensure seamless integration between planning, motion, and controls teams.
  
  

What we're looking for:

• Extensive experience building production-grade applications, tools, and pipelines using Python.
• Comfortable navigating and contributing to large, complex codebases where modularity and documentation are key.
• Proven track record of delivering software in a production environment, including familiarity with CI/CD, version control at scale, and rigorous release cycles.
• Curious about data and possess the ability to extract meaningful patterns from noisy, high-dimensional datasets.
• Passionate about a driverless future and understand the high stakes of deploying software that interacts with the physical world.
  
  

Bonus Points(not required): 

• Experience with C++ in a Linux environment.
• Familiarity with Machine Learning frameworks or Large Language Model (LLM) integration.
• Background in robotics middleware (ROS, DDS) or autonomous systems.
  
  

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:

Reporting to the Senior Business Development Manager the Strategic Partner Lead, Customer Success will be responsible for identifying, building, and nurturing strategic partnerships that drive growth and expand opportunities with key commercial partners. 

This is a pivotal time to join Motional. We are transitioning from development to deployment, launching our commercial driverless service in Las Vegas in 2026. In collaboration with a major ride-hail partner, we are setting the stage to scale this technology to dozens of cities across the U.S. and internationally. This role requires a leader with a proven track record in forging successful alliances, negotiating complex agreements, and managing relationships with key stakeholders. You will serve as the "Voice of the Customer," owning the relationship at all levels of the organization, playing a critical role in shaping our commercial strategy and achieving our long-term objectives, ensuring our commercial operations translate into scalable, revenue-generating reality. 

This role will be expected to travel up to 40% of the time depending on the business purpose and partnership deliverables.

What you'll be doing:

• Own the Partner Relationship: Serve as the primary commercial owner for critical accounts, navigating complex stakeholder maps to connect internal leads with their external counterparts. You will drive account health, retention, and efficiency by ensuring the right people are connected at the right time.
• Drive Cross-Functional Alignment: Act as the operational bridge between Commercial and technical execution teams (Product, Ops, TPM). You will translate high-level commercial milestones into clear directives, ensuring workstreams converge on time for successful deployments.
• Lead Strategic Collaborations: Establish the partnership's rhythm of business, including Quarterly Business Reviews (QBRs), Steering Committees, and executive briefings. You will lead internal alignment to ensure high-stakes partner events and demos are executed flawlessly.
• Define Success & Track KPIs: Define what winning looks like for both Motional and our partners. You will track and report on key performance indicators across teams to ensure we are meeting contractual obligations and commercial goals.
• Support Market Expansion: Lead the rollout strategy for new launch markets, coordinating logistics between Operations, Strategy, technical teams and external partners. You will drive the readiness efforts required to move from pilot zones to full commercial scale.
• Create Data-Driven Feedback Loops: Translate partner insights—such as pickup/drop-off friction—into actionable engineering requests. You will close the loop between commercial reality and technical roadmaps to optimize the end-to-end passenger experience
  
  

What we're looking for:

• Bachelor's degree in Business, Engineering, or equivalent field, or commensurate professional experience.
• 7+ years relevant professional experience in a similar role, experience working with autonomous vehicles, ride-hail, robotics or mobility industries.
• Cross-Functional Leadership: You have a proven ability to coordinate complex projects across technical and non-technical teams. You can translate commercial needs into clear directives for Product and Operations.
• Executive Presence: You possess superb communication skills and can command a room. You are experienced in leading executive presentations, QBRs, and high-visibility partner visits with polish and professionalism.
• Strategic & Operational Balance: You can set the long-term vision with a partner while also sweating the details of a short term project. You understand how to align daily execution with multi-year commercial objectives.
• Analytical & Influential: You can use data to build a compelling point of view that influences internal stakeholders. You know how to advocate for the partner’s needs to shape our long-term product strategy.
• Soft skills that earn the confidence of leaders and peers, including empathy, organization, clear communication, influencing without authority, low ego, and the ability to build trust.
  
  

Bonus Points(not required):

• MBA or equivalent advanced business degree.
• Launch Experience: Experience coordinating the commercial side of a product launch in a physical market.
• Commercial Fluency: Experience supporting business development efforts, contract renewals, or opportunities.
  
  

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

What we're looking for:

Mission Summary:

As a Principal Engineer within the Platform Engineering group, you will serve as the primary architect for Motional’s global cloud and hybrid infrastructure. Your mission is to evolve our current R&D environment into a hardened, cost-efficient, and scalable commercial backbone. You will lead the technical strategy for our hybrid cloud migration and ensure our internal frameworks provide  the velocity required for rapid AV deployment.

What you’ll be doing:

• Architect and drive the execution of our hybrid cloud strategy. You will design the networking, security, and compute abstraction layers that allow seamless workload mobility between on-premises high-performance computing (HPC) and AWS.
• Serve as the primary architect for our Kubernetes-based developer framework. You will identify and implement core improvements to the framework to enhance scalability, cost tracking and access control, reduce configuration complexity, and increase developer velocity.
• Lead organization-wide initiatives to harden service reliability. You will define the standards for observability, failover strategies, and production-grade stability across all platform-layer services.
• Prototype and deploy GenAI-focused tooling and agents to automate Platform Engineering tasks. This includes leveraging LLMs for automated incident response, predictive infrastructure scaling, and intelligent log analysis.
• Act as the final technical authority for infrastructure decisions, ensuring all new platform services align with long-term scalability and security goals.

What we’re looking for:

• Bachelor's or Master's in Computer Science, Engineering, or a related field (or equivalent practical experience)
• 12+ years in Software or Infrastructure Engineering, with significant experience in a Principal or Architect capacity
• Deep, expert-level knowledge of Kubernetes internals and ecosystem (EKS, Operators (KubeRay, ArgoWorkflow, Airflow), Service Mesh, GitOps)
• Proven track record of designing and migrating complex workloads between on-prem data centers and AWS
• Experience with Infrastructure-as-Code (Terraform/CloudFormation, Terraform Cloud/Spacelift/Atlantis) and advanced observability tooling (OpenTelemetry, Prometheus, Grafana, Datadog)
• Expert in architecting AI-driven operations, leveraging LLMs and agentic workflows to automate incident response, predictive scaling, and intelligent system observability
• Demonstrated ability to influence technical roadmaps across an entire engineering organization and mentor senior technical staff.

Bonus Points (not required):

• Expert-level experience managing and architecting solutions using Equinix datacenter products and services (e.g., Equinix Fabric, Network Edge, Metal) to enable high-speed hybrid cloud connectivity (AWS Direct Connect)
• Prior experience in the Autonomous Vehicle, Robotics, or large-scale IoT/Fleet Management industries.
• Experience leading technical projects in a globally distributed team
• Proven expertise in CI/CD orchestration, build systems (Bazel), 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:

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.

Mission Summary:

We are seeking a capable and highly motivated Engineer for our Developer Platform team to enable rapid and safe software delivery by providing a unified, efficient and reliable platform for all developers at Motional. You will join a talented team of engineers that focuses on improving the engineering experience and developer productivity of teams in Motional by providing them with the necessary tools and processes. You will collaborate closely with teams across the organization to identify pain points and drive initiatives that empower teams to deliver on Motional’s mission.

Your main focus will be on our real-time data pipeline which enables our AVs to communicate with our cloud services such as Command Center, Over-The-Air update systems, and ride hailing partners integration.

This is a remote-first position based anywhere in the U.S. 

What you'll do:

• Design, build, document, test, and maintain network, compute, and storage infrastructure of our cloud platform for the AV fleet.
• Monitor, support, and resolve issues as they arise in production.
• Assist with high-level analysis, system design, and code reviews.
• Communicate with stakeholders and team leads to identify system requirements.

What you'll be working on:

• Observability systems, CI/CD pipelines for integrations with ride hailing partners like Uber and Lyft.
• Cost Optimizations, Performance Optimizations, Security Improvements of Cloud Systems.
• Automation, services and LLM-integrated bots to reduce developer toil.

What you bring:

• 2+ years of professional work experience as a Software Engineer/DevOps in designing and building distributed systems.
• Experience with Golang / Python.
• Experience with AWS (EC2, EKS, ECS, Lambda, VPC, S3, IAM, IOT).
• Knowledge of CI/CD tools (e.g. GitLab CI, Jenkins).
• Experience with Infrastructure as Code (Terraform).
• Comfortable taking projects from ideation through to completion, with strong communication and collaboration across multiple international teams.
• Comfortable working in a fast-paced, continuous delivery environment.

Bonus points for experience with:

• Working with a globally distributed team.
• Experience with serverless architectures, building systems using SQL and NoSQL databases.
• Experience with time-series databases and monitoring tools (Prometheus, VictoriaMetrics, Grafana, Redash).
• Experience with GenAI solutions (Q Developer/Business, Gemini).
• Experience in Site Reliability Engineering.
• Experience with error monitoring software (Sentry, Incident.io).

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 AI Data Foundry is the vital link between our company's expansive data and the engineering teams that rely on it. We architect and operate the core services and infrastructure necessary to transform petabytes of raw data each month into actionable insights for our Machine Learning and Autonomy engineers. This role is a key contributor across our core initiatives:

• Data Processing: We are building state-of-the-art infrastructure to meet the demands of our rapidly scaling fleet and sophisticated ML engineering requirements. You will be responsible for ensuring that our core data pipelines are robustly engineered—meaning they are performant, user-friendly, and highly fault-tolerant.
• Data Discovery: we are building a platform that combines cataloging data for search needs across our metadata stores, vector datastores, and various data warehouses to super charge our ML pipelines. You would be coming in and working with ML and autonomy stakeholders to build out this new discovery platform. 
• Data Lineage: we are getting started with building our data lineage system that will track the usage of all data at Motional. You would work with our stakeholders to ensure our system is widely adopted and address customer pain points.

What You'll Be Doing

• Play a key role in designing and building the next generation of data infrastructure.
• Build scalable backend services for data discovery and data lineage systems.
• Write high quality, maintainable code to process petabytes of data 
• Lead and champion high-level system design and quality code reviews/technical contributions.
• Design, build, and maintain scalable data processing and access with cloud ETL technology.

What We're Looking For

• 3+ years of professional experience as a data engineer or data pipeline engineer
• BS or MS in Computer Science or related field
• Strong development experience with Python and SQL.
• Expertise with AWS services and solutions (EKS, Lambda, ETL) 
• Experience with distributed system design and development
• Comfortable working in a fast-paced, continuous delivery environment

Bonus Points (not required): 

• Experience with Infrastructure Monitoring
• Experience working in cross-functional development teams 

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.

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:

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.