Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Software Engineer on the Machine Learning Data Engine: Labels Platform team. Our team is responsible for production services supporting high volume data labeling operations. We also provide data models and service interfacing supporting a variety of autonomy data consumers. Autonomy performance is directly dependent on data quality, selection, and volume. On this team you will have opportunities to work on projects that are mission-critical for the company. You will also have the opportunity to develop innovative industry-leading ML Ops solutions. Aurora is uniquely positioned to lead in this space due to its end-to-end data collection, labeling, model training and evaluation toolchain.

In this role, you will

• Apply production best practices to ensure platform reliability
• Feature development for new labeling applications
• Collaborate across teams and functions (product, program, operations, data science) to drive projects from inception to delivery
• Apply ML Ops best practices to design processes for improving data coverage and quality

Required Qualifications

• BS / MS / PhD degree in Computer Science or a related field
• For non-CS majors or BS candidates, strong software experience (4+ years in industry)
• 4+ years of expertise with production backend services (Cloud, Kubernetes, DevOps)
• Experience with C++ and Python

Desirable Qualifications

• Relevant domain knowledge: data annotation, autonomous driving, computer vision, robotics, mapping, numerical computing, 3D graphics
• Specific technology: AWS, Terraform, Bazel, Docker, Kubernetes, gRPC, SQL, Elasticsearch
• Supplementary programming languages: Golang, Typescript

The base salary range for this position is $126,000 - $201,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#LI-JL261

#Mid-Senior 

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Technical Product/Program Manager to join Aurora’s Product & Program Management team, partnering closely with the Behavior Planning team as well as Software development teams (i.e., Data Engine, Controls, etc.) broadly.  The Behavior Planning team is an integral part of Aurora’s Driver team and is responsible for developing the algorithms for selecting safe and comfortable trajectories for the Aurora Driver.

In this role, you will

• Partner deeply with Behavior Planning leads and engineers to plan and prioritize development with greatest product impact.  
• Assess requirements, facilitate selection of the best options, and coordinate the team to successfully evolve tools and operational processes to achieve them.
• Track progress, resolve dependencies, evaluate risks and communicate status to upper management and project stakeholders, and engage and energize the project teams to achieve aggressive goals.
• Manage complex projects at a large scale, spanning many functional teams and cross-functional initiatives. Instill an efficient project management mindset and workflow across the team, and function as a go-to resource for project management mentorship
• Remove obstacles to drive momentum and progress, identify gaps in communication or schedule, manage issue escalations and provide support to teams balancing competing priorities, and drive results proactively.
• Understand technical implementation at the architectural level and propose technical alternatives when necessary; ask questions that clarify priorities and push the team to be effective.

Required Qualifications

• Minimum of 7 years experience as a Technical Program Manager, Product Manager, or Engineering Manager, or Engineer in an autonomous systems, robotics, data science, machine learning, computer vision, or software development environment.
• Bachelor’s degree in Engineering, Computer Science, Math, Data Science, Information Systems or a related area, or the equivalent in experience with evidence of exceptional ability preferred. 
• A strong familiarity with machine learning models, robotics or computer vision systems and their architecture.
• Direct, measurable impact through the design, development and launch of groundbreaking products or delivery of significant and novel technology programs.
• High technical aptitude with an ability to understand technical designs, software development lifecycle, challenges and risks; ability to work closely with engineers.
• Strong experience in project management; practical familiarity with both Agile and Waterfall methodologies and ability to apply them where best suited.
• Strong written and verbal communication skills with the ability to adjust communication based on audience. 
• Passion for shipping new to market products and the ability to dynamically adapt to new responsibilities needed to do so

The base salary range for this position is $163-$236K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-SP1

#Mid-Senior 

How You'll Make an Impact: 

As a Senior Fullstack Engineer on the Distribution Team, you'll be instrumental in developing and enhancing the products that connect Cloudbeds' ecosystem to the world's largest distribution channels. You'll architect scalable solutions using modern technologies, contribute to our microservices migration, and ensure our platform delivers exceptional performance and security for thousands of properties worldwide. Your work will directly impact how hotels reach guests through integrations with major platforms like Booking.com, Airbnb, and beyond.

Our Distribution Team:

We're the bridge connecting properties to the global travel ecosystem. Our team tackles complex integration challenges that directly impact revenue for thousands of hotels worldwide, from building rock-solid connections with major OTAs to ensuring every booking flows seamlessly and securely. We balance innovation with pragmatism: migrating legacy systems to modern microservices while maintaining the reliability our customers depend on. If you thrive on solving hard technical problems with real business impact and love the challenge of both building greenfield features and refactoring legacy code, you'll feel right at home here.

What You Bring to the Team:

• Design and implement robust backend features and improvements using PHP, with a strong focus on performance optimization and scalability for our distribution platform
• Build intuitive frontend experiences using React and Vue, ensuring seamless user interactions across the Cloudbeds ecosystem
• Architect secure solutions for handling financial transactions and sensitive personal data, applying security best practices throughout the development lifecycle
• Write clean, well-tested, and well-documented code with comprehensive test coverage (unit, integration, end-to-end) to maintain high-quality standards
• Lead technical discussions on complex concepts and requirements with both technical and non-technical stakeholders, driving alignment on backend and frontend architecture decisions
• Contribute to our ongoing initiative to migrate core platform components into microservices, helping shape the long-term technical vision
• Re-architect and refactor existing legacy systems to align with modern standards and project requirements, demonstrating ownership and commitment to continuous improvement
• Mentor team members through pair programming and code reviews, promoting best practices that elevate code quality and team processes
• Collaborate with cross-functional teams to plan, build, and ship high-quality features that delight our global customer base

What Sets You Up for Success:

• 5+ years of PHP web application software engineering experience
• 5+ years of experience with JS frameworks, Vue.js and React are preferred
• Solid experience with modern JavaScript/TypeScript
• Strong hands-on experience with Docker and containerized development workflows
• Demonstrated expertise in performance optimization and expert knowledge of relational databases, indexing, and searching technologies
• Strong understanding of security considerations, particularly for applications handling financial transactions and personal data
• Experience with test automation across all levels (unit, integration, end-to-end) and a passion for quality-driven development
• Proven track record of taking ownership of projects and delivering results independently
• Business-level English fluency (verbal and written) and excellent communication skills for collaborating across a globally distributed, remote-first team

Bonus Skills to Stand Out:

• Experience designing and building microservices and/or micro-frontends
• Hands-on experience with PHP frameworks (CodeIgniter, CakePHP, Laravel, Symfony)
• Cloud and infrastructure experience with Kubernetes, AWS, Terraform, and Argo CD
• Experience working with event-driven architectures and messaging systems (e.g., Kafka)

Compensation: Depending on your skills and experience, you can expect your annual compensation to be between $145,000 - $165,000

#LI-IK1

We’re searching for a talented Systems and Safety Engineer to make an impact on the verification of the autonomous vehicle (AV) sensing capabilities. In this role, you will have the opportunity to define and validate the sensing capabilities of the Aurora Driver to a level of super-human performance and safety. You will work with world-class engineers in Aurora Driver software teams to meet the ambitious product goals at Aurora while maintaining a high bar of safety as we expand across lanes, platforms, environments, and other technical challenges at large scale.

In this role you will

• Own the definition and allocation of requirements within a sensing capability,  understanding impacts to interfacing modules, with appropriate decomposition and traceability
• Perform impact analysis that supports product expansion as it relates to requirements, coverage, and risk due to sensing capabilities
• Collaborate closely with Product, Operations, and Autonomy teams to elicit sensing requirements from product definitions and system-level requirements and use cases
• Perform safety analyses (such as HARA, FMEA, STPA etc.) to understand the safety and any risk associated with sensing capabilities
• Define and execute comprehensive Verification & Validation (V&V) activities
• Perform detailed data and kinematics analysis to rationalize the desired requirements and test coverage
• Support requirement management workflows, traceability, and tooling
• Facilitate cross-functional co-development activities and working groups including support to design reviews, reconciliation of requirements, and producing high quality documentation.
• Develop and obtain cross functional alignment on novel approaches for systems and safety engineering work

Required qualifications

• Degree in Mechanical, Electrical, Aerospace Engineering, Computer Science, Robotics, or a related field
• 3+ years of experience in systems engineering, safety engineering, or a related field
• Experience writing verifiable functional and non-functional requirements, preferably in autonomous systems
• Experience in a safety critical industry and software development standards, software safety fault/hazard analysis, and requirements-driven software verification and validation strategies
• Proven ability to work in high-ambiguity environments with evolving priorities, while managing diverse stakeholders across software, product, and operations teams
• Excellent communication and presentation skills

Desirable qualifications

• 5+ years experience deploying safety-critical features or products at scale
• Demonstrated proficiency in the application of ISO 26262, ASPICE, and ISO 21448 (SOTIF)
• Familiarity with the applications of Artificial Intelligence or Autonomous Systems technologies (e.g., Reinforcement Learning, Deep Learning, Machine Learning) to sensing, perception, multi-unit planning, or command and control of autonomous systems
• Familiarity with modern software development practices and designs, unit testing, integration test, and release processes
• Experience with various testing modalities and strategies

The base salary range for this position is  $126,000 - $181,000 per per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We're searching for a Staff Security Engineer to join our Enterprise Security Engineering team, reporting to the Technical Lead Manager of Security Engineering.

Aurora is scaling its autonomous trucking operations, and the security foundations protecting our employees, devices, internal systems, and data need to scale with us. We're looking for a deeply technical enterprise security engineer who is as comfortable in a code editor as in a security console — you build the systems that make Aurora's security operations possible. This is a role for someone who can architect robust enterprise security solutions, write the code to implement them, and partner across Engineering and IT to make sure security is embedded from the start, not bolted on at the end.

This is not a security operations-only role. It sits squarely in enterprise security engineering, where the work is designing, building, and owning the platforms, integrations, and automation that power Aurora's internal security posture at scale.

In this role you will

• Own the architecture and implementation of Aurora's enterprise security controls — designing the systems and integrations that protect Aurora's endpoints, identities, internal infrastructure, and SaaS environment.
• Design and build Aurora's security telemetry and detection infrastructure, including log pipelines, SIEM integrations, and alerting frameworks — in partnership with the Security Operations Engineer who owns ongoing tuning and rule development.
• Define and enforce enterprise security standards, conducting architecture and design reviews to ensure alignment with Aurora's security posture and risk tolerance.
• Partner with IT, Infrastructure, and Engineering teams to embed security requirements early — shifting left on corporate IT initiatives before they become technical debt.
• Build automation and tooling that extends the capabilities of Aurora's security platforms, reduces manual operational burden, and scales the team's impact.
• Serve as the escalation point for enterprise security incidents requiring engineering-level investigation or remediation, and participate in the team's on-call rotation.
• Translate security strategy into concrete, executable engineering projects with clear milestones and measurable outcomes.

Required qualifications

• 12+ years of hands-on experience in enterprise security engineering or corporate information security — specifically securing employee-facing systems, endpoints, identities, and internal infrastructure (not product or application security).
• Proficiency in at least one programming language, used in a security context — writing production-quality automation, integrations, or internal tooling (the team primarily uses Go; Python is also common).
• Experience architecting and integrating enterprise security platforms — designing API integrations, automating workflows, and building tooling that extends platform capabilities across domains such as EDR/XDR, MDM, IAM/IGA, DLP, SaaS security, cloud security, or PKI.
• Experience designing and building security telemetry pipelines and detection infrastructure — log ingestion, normalization, SIEM integration, and alerting architecture.
• Experience leading cross-functional security engineering projects — defining scope, driving execution, and aligning stakeholders across Engineering and IT.
• Track record of conducting security architecture reviews and translating findings into actionable, risk-prioritized remediation plans.
• Experience evaluating security posture and identifying systemic gaps, with a bias toward building durable solutions rather than one-off fixes.

Desirable qualifications

• Experience with Zero Trust architecture and identity-centric security models (BeyondCorp-style or similar).
• Familiarity with NIST CSF, MITRE ATT&CK, and CIS Benchmarks as engineering inputs — used to inform what to build and how to validate it, not just as compliance checkboxes.
• Hands-on AWS security experience (SCPs, GuardDuty, Security Hub, IAM, etc.) and familiarity with integrating cloud security signals into a corporate security platform.
• Experience with applied cryptography and PKI in a production enterprise environment — certificate lifecycle management, CA design, or secrets management.
• Familiarity with securing AI/ML platforms or applications built on LLMs, RAG pipelines, or MCP-based architectures.
• Security certifications such as CISSP, GCED, GREM, or similar (valued but not required).

The base salary range for this position is $171,000 - $247,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#Mid-Senior 

What we are looking for

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all.

We’re searching for a Software Engineer II to join the Control Simulation team and help transform how we validate and improve the safety and performance of the Aurora Driver.

In this role, you will operate at the intersection of Machine Learning, Software Engineering, Data Science, and Vehicle Dynamics. You will contribute to the development of our next-generation data driven vehicle simulator, build data pipelines that source critical scenarios from our fleet and generate simulations from logs, and analyze data to prove the safety of our motion control software.

This is a high-impact role for an engineer who enjoys a mix of model development, infrastructure building, and data analysis.

In This Role You Will:

• Develop Vehicle Models: Help design and implement our next-generation differentiable vehicle dynamics simulator for controls V&V.
• Build Simulation Pipelines: Design and maintain the software pipelines required to generate "Sim-from-Log" scenarios. You will ensure that high-value on-road events are systematically converted into reproducible simulation tests.
• Implement Control Scenario Taxonomies & Curate Data: Build the data structures and algorithms to categorize complex control scenarios (e.g., maneuvers, environments) and use this framework to source balanced datasets from on-road logs, ensuring comprehensive ODD coverage for model training.

Required Qualifications:

• BS or MS in Computer Science, Robotics, Data Science, or a related engineering field.
• 2+ years of software engineering experience with a focus on data-intensive applications or machine learning.
• Strong proficiency in Python (including libraries like Pandas, NumPy, Scikit-learn).
• Hands-on experience with PyTorch or similar machine learning frameworks.
• Experience working with large datasets, SQL, and data processing pipelines.
• Strong analytical skills with the ability to translate complex data into actionable engineering insights.
• Background or interest in Control Theory or Vehicle Dynamics (understanding of kinematics, kinetics, and actuation).

Desirable Qualifications:

• Experience with machine learning or system identification for physics based-models.
• Familiarity with V&V methodologies, simulation frameworks, or log analysis tools.
• Experience building data visualization tools or dashboards to track software quality and coverage.
• Proficiency in C++ (necessary for integrating with on-vehicle or production codebases).

The base salary range for this position is $126,000-$181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-KW1

#Associate

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We’re searching for a Software Engineer to join Aurora’s Behavior Planning ML Platform team.  Our team is responsible for building both the offline pipelines to train and evaluate models and the infrastructure to efficiently run these models onboard the vehicle. On the offboard side, we build and support  the large scale distributed pipelines that model developers rely on to source data at scale, train, and evaluate machine learning models. On the onboard side, we build and maintain the on-vehicle infrastructure required to deploy these models and run inference in a soft real-time system.

In this role, you will

• Develop large scale pipelines for data extraction, model training and model evaluation
• Build and optimize onboard ML infrastructure used to deploy models and run inference onboard the vehicle
• Collaborate closely with motion planning, systems engineering, and other autonomy groups to define and develop critical ML workflow requirements.

Required Qualifications

• BS or higher degree in Computer Science/Engineering or related fields. > 6 months of experience
• Strong programming skills in C++ or Python, ideally both
• Experience with machine learning frameworks (PyTorch or TensorFlow)
• Solid foundation in computer science fundamentals - especially operating system concepts including concurrency, memory management and process scheduling.

Desirable Qualifications (this section is optional)

• Experience with GPU programming and Nvidia profiling tools - CUDA, NSight Systems, Nsight Compute
• Experience working in cloud compute (AWS, Azure, GCP) ideally with batch processing or other large-scale workflow management platforms. 
• Experience profiling and optimizing software on Linux

The base salary range for this position is $126,000 - $181,000 per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

#LI-JL261

#Mid-Senior 

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. 

We’re searching for a Senior software engineer to join Aurora’s Vehicle Data Management team. The Vehicle Data Management Team is responsible for offloading, ingesting and scaling data through various pipelines, including autonomy sensor data, vehicle logs, sims, models, and training sets. The ideal candidate will design and implement systems that efficiently work for both physical offloaders and cloud, and also be an effective liaison between onboard system to cloud system.

In this role, you will

• Architect and implement on-vehicle/offload + cloud data systems that scale to hundreds of PB of multimodal data (sensor/log/sim/ML datasets).
• Improve reliability and performance of offline data workflows: throughput, latency, and discoverability (indexing/metadata/search).
• Build internal tooling, libraries, and operational patterns that make data pipelines  evolve and scale.
• Own key services end-to-end (design, implementation, rollout, on-call/operations, observability, and incident response).
• Partner directly with stakeholders across onboard systems, autonomy, ML, and infrastructure to deliver pragmatic solutions.

Required Qualifications

• BS/MS or PhD in Computer Science or a related field
• Minimum 3-5 years related experience
• Required programming skills: GoLang/Python
• General knowledge of backend software systems networking, load balancing, API gateways, system security, gRPC services.
• AWS infrastructure experience, including S3 and DynamoDB in a production commercial system
• Knowledge of database design, database management and database scalability.

Desirable Qualifications

• Proficiencies with coding in C++ 
• Proficiencies with Linux system 
• Experience with large scale distributed systems or microservice architectures
• A passion for writing robust, intuitive, high-performance code, and being pragmatic about it
• Ability to navigate and work efficiently in large codebase 
• Strong software development background demonstrated by industry experience in building platforms that serve AV development and commercialization.

The base salary range for this position is  $146,000 - $234,000 per Year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

 #LI-#Mid-Senior 

Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. 

The journey to developing our cutting-edge self-driving truck Driver software requires a massive and continuous computational effort. Every day, Aurora's engineers initiate and manage millions of compute tasks, systematically processing and analyzing petabytes of critical data. This colossal computational workload spans various essential domains, including raw and derived data processing pipelines, large-scale simulations to test and validate the software in countless scenarios, and the intensive machine learning training jobs that are the core of our autonomous system's intelligence.

At the heart of orchestrating this monumental compute infrastructure is the Compute team. This team is dedicated to building and maintaining the foundational technology that solves the fundamental challenges of resource scheduling, task isolation, and distributed state consistency across our massive batch compute fleet. At our scale, traditional off-the-shelf orchestrators break. The Compute team builds the custom engine - BatchAPI - that manages the lifecycle of millions of tasks - built on top of K8s primitives but implements our own custom scheduler.

We deal with the 'unsolved' problems of distributed computing: maximizing hardware utilization while ensuring that a failure in one node doesn't cascade across the entire cluster. This engine is engineered to handle massive scale, ensuring reliability, efficiency, and rapid turnaround for our engineers.

Furthermore, the Compute team empowers engineers across the company to effectively harness this compute power. They develop and maintain the Batch Workflows Python SDK. This framework provides an intuitive, high-level interface that allows engineers to programmatically define, construct, deploy, monitor, and manage their complex computational workloads. The SDK abstracts away the complexities of the underlying infrastructure, enabling engineers to focus purely on the logic and goals of their data processing, simulation, or training tasks, thus accelerating the entire development cycle for the Aurora Driver.

In this role you will

• Design, implement, and maintain core components of the high-performance, large-scale distributed batch compute engine (BatchAPI). Architect and optimize the scheduler, resource allocator, and execution engine of BatchAPI to handle bursty, heterogeneous workloads with minimal overhead.
• Design low-latency APIs and resilient communication protocols that bridge our Python SDK with the Golang-based core engine.
• Develop high-level workflow abstractions, enabling engineers across the company to programmatically define, deploy, and manage complex data processing, simulation, and ML training pipelines. 
• Solve complex problems in distributed locking, throttling, and fair-share scheduling to ensure multi-tenant stability.
• Drive continuous improvements in the performance, scalability, and resilience of the entire compute infrastructure, implementing robust monitoring and alerting systems to maintain operational excellence for critical workflows.
• Collaborate closely with infrastructure and product engineering teams (e.g., Autonomy, Data, Simulation, Machine Learning) to gather requirements, provide expert consultation, and integrate compute workflows with key company systems.

Required qualifications

• 5+ years of professional software engineering experience.
• Deep expertise in Golang (for core systems) and Python (for SDK/API layering).
• Strong understanding of distributed systems fundamentals (e.g., CAP theorem, consensus algorithms, or gossip protocols).
• Experience with performance profiling and tuning (e.g., memory management, I/O bottlenecks, or network latency optimization).
• Specialized knowledge of container orchestration systems like Kubernetes.
• Proven track record of driving continuous performance, scalability, and resilience improvements in production environments managing critical data.
• Familiarity with cloud provider compute and data services (e.g., AWS EKS, S3, RDS).

Desirable qualifications

• Experience working with computational workloads specific to the autonomous vehicle, robotics, or large-scale machine learning domains (e.g., data processing for perception, simulation, or model training).
• Demonstrated ability in creating and refining user-facing tools, including adeptness at incorporating user feedback, managing expectations, and effectively prioritizing development based on user needs.
• Web UI development experience (Typescript, React)

 #LI- #Mid-Senior 

The base salary range for this position is  $146,000 - $234,000 per year. Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits.

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 Staff Machine Learning Engineer, you will serve as a technical leader defining the roadmap and architecture for the machine learning systems that power our data discovery and model improvement lifecycles. Rather than focusing on a single specialized domain, you will leverage your broad ML expertise to architect massive, scalable systems, from multimodal representation learning and active learning loops to hyper-efficient production inference. You will own system-level architecture, lead multi-quarter, multi-person initiatives, and partner across the engineering organization to unblock teams and influence our department-wide technical strategy. By establishing robust processes and mentoring those around you, you will ensure our ML platforms act as a reliable, mission-critical engine for the entire autonomy stack.

What You'll Do:

• Define Technical Strategy & Roadmaps: Develop and execute multi-quarter, high-impact technical roadmaps for core ML systems. Proactively inform leadership to guide reprioritization, ensuring initiatives consistently drive team-wide and department-level OKRs and KPIs.
• Architect System-Level Solutions: Own the system-level architecture for complex ML products. Design scalable frameworks for massive data mining and highly optimized, real-time inference across GPU/CPU clusters.
• Drive Cross-Functional Execution: Lead multi-person projects to completion across teams. Influence partner teams' technical roadmaps (such as Autonomy) to solve shared problems, break down silos, and build alignment.
• Elevate Engineering Excellence: Establish department-wide standards for ML system design, code quality, testing, and deployment. Deliver processes to proactively address issues and participate in org-wide incident response planning.
• Operate as a Generalist Expert: Apply a broad toolkit of ML techniques (deep learning, representation learning, active learning, generative AI) to solve complex, ambiguous problems. Unblock yourself and your team when facing unprecedented technical challenges.
• Mentor and Lead: Act as a role model and technical go-to person. Coach Senior and junior engineers, lead architectural reviews, and elevate Motional’s engineering culture through internal documentation, tech talks, and collaborative design.
  
  

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

• BS in Computer Science, Machine Learning, or a related field (or equivalent practical experience)
• 8+ years of hands-on ML engineering experience, with a proven track record of owning architecture, deployment, and optimization of large-scale ML systems
• Demonstrated experience working with multimodal foundation models in ML production systems, including integration, scaling, fine-tuning, or deployment of models that process multiple data modalities (e.g., camera, LiDAR, radar, text)
• Demonstrated technical leadership: defining multi-quarter roadmaps, leading multi-person initiatives, and driving department-level technical strategy
• Expert-level proficiency in Python and ML frameworks (PyTorch, TensorFlow, or JAX), backed by strong software engineering fundamentals (system design, CI/CD, containerization)
• Broad ML generalist knowledge, with practical experience spanning model training, deep learning architectures, evaluation methodologies, and production deployment at scale
• Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and optimizing for latency, throughput, and hardware efficiency
• Proven ability to mentor peers, explain complex trade-offs to leadership, and drive consensus across disparate teams
  
  

Bonus Points (Nice-to-Haves):

• MS/PhD in Computer Science, Machine Learning, or a related field.
• Background in autonomous driving, robotics, or complex real-time decision-making systems.
• Experience with massive-scale ML data mining, active learning loops, and contrastive/representation learning.
• Familiarity with multimodal learning, sensor fusion, or large foundation models.
• Deep knowledge of model serving tools (TF Serving, Triton, TorchServe) and enterprise MLOps platforms.
• Demonstrated experience leading org-wide severity reviews or establishing incident response planning for mission-critical ML platforms.
  
  

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:

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

Company Description

Govini transforms Defense Acquisition from an outdated manual process to a software-driven strategic advantage for the United States. Our flagship product, Ark, supports Supply Chain, Science and Technology, Production, Sustainment, Logistics, and Modernization teams with AI-enabled Applications and best-in-class data to more rapidly imagine, develop, and field the capabilities we need. Today, the national security community and every branch of the military rely on Govini to enable faster and more informed Acquisition decisions.

Job Description

We are seeking an experienced Lead AI Engineer to lead our Agentic AI team as we scale our agentic offerings across all levels of the US government. Over the past year, we have seen the rapid adoption of our agent, Ace. We expect Ace to be handling much more complex tasks and workflows end-to-end and/or in cooperation with a human user as time goes on. The team is striving to make Ace an even more effective agent, focusing on planning, reliable execution over longer time horizon tasks, scaled tool use, Ace Skills, memory, and inter-agent coordination.

In order to do this job well, we are looking for someone who can demonstrate a project built on LLMs that showcases your skill at getting them to do complex tasks.

• Experience leading agentic system development from ideation through production, including technical design, architecture decisions, and day-to-day leadership of Data Scientists and Machine Learning Engineers
• Experience integrating and working with LLMs, with a strong understanding of their capabilities and limitations
• Experience integrating and working with agent frameworks like Claude Agent SDK or OpenAI Agent SDK
• Experience building observability, evaluation, and feedback loops for agent behavior (telemetry, prompt evaluation, regression testing, and reliability metrics).
• Experience working in highly ambiguous environments, and operating with urgency
• Lead Agile ceremonies and technical planning for the Agentic AI team

Strong Candidates have:

• Experience designing and deploying complex agentic systems using LLMs
• Hands-on work with multi-agent coordination, routing, and tool orchestration
• Passion for building autonomous and semi-autonomous systems that solve real customer problems

This role is a full-time position located out of our office in Pittsburgh, PA. 

This role may require up to 10% travel

Scope of Responsibilities 

• Designs and builds multi-agent systems with tool use, memory, routing, and planning
• Develops Agent Skills and tools as modular, composable services that interact with backend systems, models, and data processing
• Assist with automated evaluation of agents, skills, and prompts across the entire product lifecycle
• Work with our Product and Implementation organizations to find solutions to our most vexing challenges applying agents to our customer problems

Qualifications

• U.S. Citizenship is required

Required Skills:

• Bachelor's, Master’s, or Doctorate in Computer Science, Computer Engineering, Data Science, or a related field
• Minimum 3 years of experience building and deploying ML or LLM-powered systems in production environments
• Minimum 2  years of experience leading or mentoring engineering teams in production environments
• Practical experience in building, developing, and productionizing machine learning systems
• Advanced software skills in Python
• Experience with common LLM algorithms and implementations
• Hands-on experience with AWS and cloud infrastructure
• A strong desire to learn and investigate new technologies
• Familiarity with Git source control management
• Ability to work collaboratively with little supervision
• A burning desire to work in a challenging fast-paced tech environment

Desired Skills:

• Current possession of a U.S. security clearance, or the ability to obtain one with our sponsorship
• Experience in or exposure to the nuances of a startup or other entrepreneurial environment
• Experience with Claude Code and GenAI coding best practices.

We firmly believe that past performance is the best indicator of future performance.  If you thrive while building solutions to complex problems, are a self-starter, and are passionate about making an impact in global security, we’re eager to hear from you.

Govini is an Equal Opportunity Employer.  All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability and protected veterans status or any other characteristic protected by law.

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.

Mission Summary:

The Staff Systems Safety Engineer:

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

Essential Duties:

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

Qualifications:

Educational Requirements

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

Technical / Specialized Knowledge, Skills, Abilities:

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

Physical Demands:

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

Working Environment:

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

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

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

Mission Summary:

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:

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 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:

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

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

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

What you’ll be doing:

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

What We’re Looking for:

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

Bonus Points:

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

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

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

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

What you’ll be doing:

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

What We’re Looking for:

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

Bonus Points:

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

Mission Summary:

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

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

What you'll be doing:

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

What we're looking for:

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

Mission Summary:

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

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

What you'll be doing:

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

What we're looking for:

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

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

Tech Lead Manager, Planning

On our Planning team, you'll apply your passion in robotics and software development for production-ready autonomous vehicles. As the Technical Lead Manager, you will direct a team tasked with the design and implementation of motion planning software for autonomous vehicles. This position requires leadership in defining the motion planning and control systems that enable our fleet to operate securely, effectively, and with passenger comfort in intricate settings. As a leader, you will drive the development of cutting-edge motion planning algorithms, collaborate with cross-functional teams (Localization, Perception, Prediction, Controls, ML Products, and Systems Engineering), and mentor a talented group of engineers to deliver state-of-the-art solutions. If you are passionate about autonomous driving, thrive on solving challenging real-world problems, and are eager to make a significant impact in a rapidly evolving field, we want to hear from you.

Role responsibilities:

• Lead and develop a team within the motion planning organization, assuming responsibility for planning algorithm and constraint generation.
• Collaborate with other leaders to provide technical direction, making critical decisions on architectural strategies, strategic resource allocation, operational execution, and technical debt management.
• Deliver a robust and scalable planner, prioritizing safety throughout the design, prototyping, testing, deployment, and production phases.
• Adopt a metrics-driven approach to the development and enhancement of technical components.
• Advance existing planning methodologies to facilitate data-driven strategies.
• Promote diversity and inclusion in both products and personnel.
• Mentor and offer constructive feedback (technical and professional) to team members, cultivating an inclusive and collaborative work environment.
• Demonstrate initiative in generating innovative ideas, formulating a team vision, and considering the holistic robotaxi system.
• Implement and review algorithms and code, applying rigorous engineering methodologies.
• Partner with project managers to develop roadmaps and execute plans according to schedule.

What we're looking for:

• Over two years of experience in the management of a development team, with a demonstrated ability to foster career growth, mentor team members effectively, and enhance productivity.
• Masters or PhD in Robotics, Electrical Engineering, Computer Engineering, Computer Science, Mechanical Engineering, or a related field.
• Established history of successfully delivering production-quality motion planner in a leadership capacity.
• Advanced proficiency in search algorithms.
• Experience in developing motion planning solutions with ML
• Expertise in C++ software development, Linux, and Python, with supplementary knowledge of SQL.
• Strong theoretical understanding and practical experience in motion planning under conditions of uncertainty, as well as in interactions with dynamic agents and environments.
• Knowledge of robotics algorithms in localization, perception, prediction, motion planning, and control systems for autonomous vehicles.
• Excellent communication, interpersonal, and management skills.

Skills appreciated

• Experience in Autonomous Vehicles or other robotics industries
• Experience using simulation tools
• Experience with Verification & Validation for safety critical systems

On Behaviors, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company.

What You’ll Be Doing:

You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include:

• Designing and executing high value experiments based on collaborative input from other machine learning engineers
• Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
• Timely release of major model updates, including analysis of both off-line and on-road evaluation data
• Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
• Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

What We’re Looking For:

• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
• Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and  testing methods
• Experience with PyTorch or other python-based deep learning frameworks
• Experience working with large data sets and deriving insights from data
• Experience mentoring and collaborating with others

Education
Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience

Bonus Points

• Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• PhD in machine learning, computer vision, or robotics vision
• Experience working on autonomous vehicles or related fields
• Experience in deploying models into real-world environments
• Strong programming skills in C++ and/or CUDA programming
• This opportunity can support remote work within the United States, with occasional travel.

Working Conditions

While performing the duties of this job, the employee is frequently required to convey and detect communication

The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment

The employee may occasionally move up to 50 pounds

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

Mission Summary:

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

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

What You’ll Be Doing:

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

Specifically, you will:

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

What We’re Looking For:

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

Preferred, but not required:

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

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

On our Behaviors team (Prediction and ML Planner), you will have the opportunity to work with world-class ML engineers, whose mission is to make self-driving vehicles a reality and to create a positive social impact. The Behaviors team develops ML models that learn how different agents navigate complex real-world traffic scenarios. We leverage these models to set the behavior of our self-driving vehicle, and predict the behavior of other agents such as vehicles and vulnerable road users. 

We are looking for proven leaders and technical experts who are passionate about Level 4 autonomous driving technology, excited by intellectual challenges, and interested in pursuing career growth with a fast-growing company.

What You’ll Be Doing:

• Define and execute motion planning and prediction projects that improve our self-driving vehicles’ capability to safely, comfortably and legally navigate complex traffic scenarios
• Lead, manage and grow a team of engineers
• Design and lead the implementation of behavior models that leverage the latest advancements in machine learning, generative AI and reinforcement learning
• Productionize and deploy solutions onto autonomous vehicle fleets
• Collaborate with perception, simulation, data platform and integration teams to validate and enhance your products’ on-road performance
• Communicate strategies, progress and challenges to executive leadership

What We’re Looking for:

• Masters or Ph.D. in Computer Science or a related technical field; or equivalent industry experience
• Proven leadership skills at executing large, complex technical initiatives
• Extensive experience managing and leading engineers
• Experience with deep learning frameworks such as TensorFlow or PyTorch
• Fluency in Python, including standard scientific computing libraries
• Proven track record of designing, developing and deploying ML solutions for autonomous vehicles or robotics
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods 
• Excellent communication and interpersonal skills

Bonus Points:

• Experience with embedded systems and real-time optimization, especially in the autonomous driving industry
• Experience with state of the art generative AI, and/or reinforcement learning, paradigms
• Proven track record of publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• Strong programming skills in C++ and/or CUDA programming

Mission:

We are seeking a highly skilled and motivated Senior Data Analysis Engineer for our large-scale AI model and software evaluation framework – Ground Truth Regression. The ideal candidate will have a strong background in data engineering, machine learning principals and statistical analysis. 

At Motional, large scale orchestration for data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of developers and deployed multiple times a day – The Ground Truth Regression team provides the large scale perception analysis framework for validating all changes to perception which can impact the autonomous vehicle behavior. 

The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis, and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UI’s. The team works together with all other perception and ML teams to develop the metrics and analyze results.

What You'll Do:

• Work with ML Engineers and Autonomy Software Developers to develop new data analysis metrics and KPI’s for the validation of the autonomous vehicle performance.
• Drive innovation by researching and developing new large scale data analysis systems.
• Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software.
• Build high-quality datasets to improve ML products through training & edge case validation.
• Provide statistical depth on model performance & generalization through rigorous error and change analysis.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Strong programming skills in Python, SciPy, and related data analysis frameworks.
• Experience in machine learning, data mining, and statistical analysis.
• Experience with large-scale data processing and distributed computing technologies.
• Strong communication and software development skills: goal setting, design documentation, test frameworks, collaborative cross team development.
  
  

Bonus Points:

• Ph.D. in Computer Science or a related field.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with machine learning in the autonomous driving domain.
• Publications or contributions to the AI/ML community.

On Behaviors, you'll have the opportunity to work with world-class ML engineers and research scientists to make self-driving vehicles a reality and create positive social impact. Our team works on the tech stack responsible for understanding highly complex driving scenes and generating safe, comfortable driving trajectories for our robotaxi using the latest deep neural networks. We are looking for engineers who are passionate about Level 5 autonomous driving, excited by intellectual challenges, and interested in pursuing career growth with a fast growing company.

What You’ll Be Doing:

You will be directly responsible for training, evaluation, and deployment of our ML-based scene understanding, behavior prediction, and planning models. Day to day responsibilities include:

• Designing and executing high value experiments based on collaborative input from other machine learning engineers
• Prototyping and implementing continuously improving metrics to evaluate the performance of our behavioral models across many desired scenarios and robotaxi capabilities
• Timely release of major model updates, including analysis of both off-line and on-road evaluation data
• Staying up to date with the latest trends in our fast moving industry, and proposing new architectures and network designs based on published literature
• Maintaining a high quality training and evaluation code-base, including portions of our training stack dedicated to dataset generation and evaluation

What We’re Looking For:

• In-depth understanding of common Machine Learning and Deep Learning algorithms
• Experience designing, training, and analyzing neural networks for at least one of the following applications: motion planning, object detection, sensor fusion, motion prediction, and/or multi-object tracking
• Strong track record of tackling less well-defined problems, and executing efficiently to deliver the successful outcome
• Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, and  testing methods
• Experience with PyTorch or other python-based deep learning frameworks
• Experience working with large data sets and deriving insights from data
• Experience mentoring and collaborating with others

Education
Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience

Bonus Points

• Publications in relevant conferences (CVPR, ICML, NeurIPS, ICCV, ICL, etc.)
• PhD in machine learning, computer vision, or robotics vision
• Experience working on autonomous vehicles or related fields
• Experience in deploying models into real-world environments
• Strong programming skills in C++ and/or CUDA programming
• This opportunity can support remote work within the United States, with occasional travel.

Working Conditions

While performing the duties of this job, the employee is frequently required to convey and detect communication

The employee occasionally required to remain stationary at times for up to 50% of working time, move in designated working areas; & operate and use office equipment

The employee may occasionally move up to 50 pounds

Mission:

We are seeking a highly skilled and motivated Principal Engineer, Technical Lead to lead our large-scale AI model and software evaluation framework – Ground Truth Regression. The ideal candidate will have a strong background in data engineering, machine learning principals and leadership, with experience in developing and deploying advanced data analysis and large scale orchestration frameworks.

At Motional, large scale orchestration for data analysis plays a critical role in delivering our ML-centered autonomous driving vehicle. Our robo-taxi ML Models and software are developed by hundreds of developers and deployed multiple times a day – The Ground Truth Regression team provides the large scale perception analysis framework for validating all changes to perception which can impact the autonomous vehicle behavior. 

The GTRegression team validates the end impact of ML and software changes to the autonomous vehicle while those changes are in development, providing the tools for Root Cause Analysis, and safety consideration. We monitor for model errors, anomalies, rare objects & long-tail driving scenarios across thousands of driving hours. The team develops the full stack – AWS Kubernetes orchestration framework, ReSimulation, model metrics, regression reports, and deep dive analysis UI’s. The team works together with all other perception and ML teams to develop the metrics and analyze results.

What You'll Do: 

• Lead a team of engineers with a diverse skill set to deliver critical software supporting the development of the autonomous vehicle ML models and software.
• Drive innovation by researching and developing new large scale data warehousing and analysis.
• Own large-scale data analysis workflows that surface unexpected impacts of planned and unplanned changes to the ML models and software.
• Build high-quality datasets to improve ML products through training & edge case validation.
• Provide statistical depth on model performance & generalization through rigorous error and change analysis.
• Provide technical leadership and mentorship to the team, fostering a culture of collaboration and continuous improvement.
• Manage project timelines, resources, and deliverables to ensure successful project execution.

What We're Looking For:

• Bachelor's or Master's degree in Computer Science, Data Science, or a related field.
• Excellent leadership, communication, and problem-solving skills.
• Proven record leading a small diverse dedicated team supporting a large user base.
• Experience in machine learning, data mining, and statistical analysis.
• Proven experience in developing and deploying large scale cloud frameworks.
• Strong programming skills in Python.
• Experience with large-scale data processing and distributed computing technologies.
  
  

Bonus Points:

• Ph.D. in Computer Science or a related field.
• Experience with cloud platforms such as AWS, Google Cloud, or Azure.
• Experience with machine learning in the autonomous driving domain.
• Publications or contributions to the AI/ML community.

Since its inception in 2014, Roivant Sciences has sought to improve health by rapidly delivering innovative medicines and technologies to patients. We’ve employed a unique, decentralized model of nimble, focused companies (‘Vants’) focused on various therapeutic areas and built around the pursuit of innovation in drug development and technology.

Our model is different. Five new medicines have been approved off the Roivant platform; we’ve built five biotechs that have become public; we’ve created well over $1b in value in Roivant Health in just six years.  Our successes have ranged from computational drug discovery to tokenized healthcare data exchange, and from novel topicals for dermatological conditions to ultrarare tissue therapies.

Roivant Health is Roivant’s platform for the creation of new technology Vants, focused on delivering improvements to human health outside of our traditional biotech platform.  In six years since inception, we’ve created eight enduring companies and over $1B in enterprise value, including the leading deidentified healthcare data exchange platform (Datavant) and a top-tier computational drug discovery company (VantAI) which has partnered with Johnson & Johnson, Bristol-Myers Squibb, and Boehringer Ingelheim. Our goal is to improve human health by rapidly discovering, developing and delivering innovative medicines and technologies to all patients. Our success is predicated on attracting and retaining top talent, generating new ideas and promoting an open and collaborative culture.

We embrace diversity across all dimensions and levels of the organization, and we strive to ensure every employee is supported in reaching their full potential. We hire motivated people with diverse backgrounds, identities, experiences and skillsets. We are committed to fostering an inclusive culture where all employees feel valued, respected and empowered to create value for patients.

Summary:

Roivant is seeking a Founding Engineer to work on the core technology underpinning new healthcare and life sciences companies. You’ll partner with business, operational, product, and/or clinical leaders to rapidly de-risk, prototype and productize new software, working at the intersection of AI, data engineering, and real-world biomedical data. This is a hands-on, highly entrepreneurial role ideal for a talented software engineer who wants to build groundbreaking health AI products.

Responsibilities:

• Contribute to technical strategy for new company formation, including scoping early technical feasibility, identifying data and infrastructure needs, and building initial proof-of-concept systems
• Design, build, and iterate on tooling, infrastructure, and workflows to run AI/ML training and inference workloads at scale across varied health × AI applications
• Develop and refine data and model pipelines that integrate multimodal health data (e.g., clinical text, omics, imaging, sensor data, etc.) for downstream AI/ML tasks
• Collaborate closely with domain experts and business stakeholders to incorporate client and commercial insights into model design and deployment

Qualifications:

• Experience building and deploying ML or AI systems in production
• Strong Python engineering skills with experience in building scalable, testable codebases
• Comfort working in fast-paced, high-ambiguity environments where requirements evolve

We are deep believers in rapid career advancement for high performers and take a flexible approach to role design, adjusting responsibilities based on individual strengths. The ideal candidate is ambitious, entrepreneurial, and comfortable with ambiguity, driven by a passion for building transformational healthcare technology. We seek individuals who embrace calculated risk-taking as essential to achieving meaningful outcomes for patients.

Base salary for this role will be determined during the interview process and will vary based on multiple factors, including but not limited to prior experience, relevant expertise, current business needs, and market conditions. The expected base salary for the role will generally be between $130,000 to $180,000 per year at the commencement of employment, but the final salary offered may be outside this range based on individual circumstances and business and market conditions. 

Base salary if hired is only part of the total compensation package, which, depending on the position, may also include other components such as discretionary bonuses, equity, and Company-sponsored benefit programs.

This position is at-will and Roivant reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance and business and market conditions.

Roivant Sciences provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws.

Senior Vision AI Engineer 
(Cognitive Vision and Industrial AI)

Location: Mid-Atlantic Region
Company: Linque
Reports to: Head of Vision AI

About Proconex

Proconex is a trusted leader in industrial automation and process control solutions, proudly serving the industry for over 75 years. With a rich legacy of delivering high-performance systems and equipment to process industries—including oil & gas, chemicals, power, and life sciences—we are now entering an exciting new chapter.

We are  building on a solid foundation of over 10 years of successful deployments with our next generation of software products. Our software solutions are designed to empower industrial operators with operational analytics, enabling smarter, more efficient, and more reliable operations. This is a unique opportunity to be part of a growth-focused team that is taking proven technology to the next level.

About the Role

Linque is expanding its Vision AI and Cognitive Automation platform focused on applying real-time computer vision and AI to industrial, biopharmaceutical, and process manufacturing environments. We are seeking a Senior Vision AI Engineer to help lead the development, deployment, and customer-facing application of advanced vision AI solutions. This role sits at the intersection of deep technical execution, platform development, and real-world industrial use cases.

Key Responsibilities

• Design, develop, and deploy production-grade computer vision and machine learning models
• Build optimized end-to-end vision pipelines for real-time and near-real-time applications
• Translate complex industrial problems into scalable AI architecture
• Collaborate cross-functionally with product, engineering, and commercial teams
• Participate in technical customer discussions, pilots, and evaluations
• Support prototypes through pilot and production transitions
• Mentor junior engineers and contribute to technical best practices

Required Qualifications

• 5+ years’ experience in computer vision and machine learning
• Strong hands-on experience deploying AI systems in production
• Proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, Keras)
• Deep knowledge of Video / Image processing tools (e.g. Mask R-CNN, ResNet, U-Net)
• Knowledge of object and anomaly detection (Autoencoders, FastFlow, Transformers)
• Tunning experience for CNNs and Vision Models (e.g., MLFlow, NVIDIA TAO, MMD, MMS)
• Mastery of model interchange and GPU acceleration (e.g. ONNX, CUDA, cuDNN)
• Experience working with image/video pipelines, container orchestration (local and cloud)
• Understanding of the full ML / AI lifecycle

Preferred Qualifications

• Experience with real-time vision systems
• Background in industrial automation or regulated environments
• Experience with edge or cloud deployment
• Ability to communicate complex technical topics clearly

Why Join Linque

• Apply AI to real industrial problems with measurable impact
• Collaborate with experienced AI and industrial leaders
• Influence the evolution of next-generation Vision AI platforms
• Flexible, growth-oriented environment

Apply today to learn more about this exciting new opportunity at Proconex, the exclusive Emerson Impact Partner for the Mid-Atlantic region!