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 Platform 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 we need someone who makes our security tools actually work, not just deployed, but deeply configured, continuously tuned, and fully leveraged. This role is for the practitioner who has spent their career living inside security platforms: the person who knows their EDR better than the vendor's own support team, who can write a SIEM query from memory, and who instinctively knows when an alert is misfiring and exactly why.

This is not a software engineering role. It's a role for an elite security operator — someone with the instincts of a seasoned SOC analyst and the technical depth to own the platforms that power detection, response, and protection at enterprise scale. If you find deep satisfaction in mastering a tool, closing a coverage gap, or hunting down a threat that nobody else noticed, this role was written for you.

In this role you will

• Own the operational health, configuration, and continuous improvement of Aurora's enterprise security platform stack — including EDR/XDR, MDM, SIEM, DLP, IAM/IGA, DNS security, Email security, and PKI — ensuring each tool is tuned, policy-complete, and delivering reliable signal.
• Develop and refine detection rules, correlation logic, and alert policies, reducing noise while ensuring Aurora maintains high-fidelity coverage against real threats.
• Conduct proactive threat hunting across Aurora's security telemetry — forming hypotheses, querying logs, and investigating anomalies before they surface as incidents.
• Serve as the deepest internal expert on Aurora's enterprise security tooling, acting as the escalation point for complex platform issues, misconfigurations, and detection failures.
• Participate in the team's on-call rotation, leading deep-dive investigations into security alerts and incidents and driving triage, containment, and root cause analysis.
• Continuously audit and validate that existing security controls are configured to actually do what they're supposed to do — not just deployed and forgotten.
• Maintain operational runbooks, detection documentation, and platform configuration records, ensuring the team can operate consistently and scale institutional knowledge.

Required qualifications

• 12+ years of hands-on experience in enterprise security operations, security platform administration, or a senior SOC engineering role — with a career built on deep operational ownership of security tooling rather than software development.
• Expert-level proficiency administering and operating at least two enterprise security platforms (e.g., CrowdStrike, SentinelOne, Splunk, Panther, Sentinel, Jamf, Kandji/Iru, Puppet, WorkspaceONE, Intune, Zscaler, Okta, Proofpoint, Wiz, osquery), with strong working knowledge across several others.
• Demonstrated ability to tune and optimize security platforms beyond out-of-the-box configurations — writing custom detection logic, adjusting policy sets, and validating control effectiveness.
• Strong log analysis and threat hunting skills: you know how to build a hypothesis, write the query, follow the thread, and know when to escalate.
• Experience conducting thorough incident investigations — triage, containment, root cause analysis, and post-incident review — and communicating findings clearly to technical and non-technical stakeholders.
• Ability to assess security control effectiveness: not just "is this tool deployed" but "is it configured correctly, covering the right scope, and generating actionable signal."
• Comfort working under pressure in ambiguous, fast-moving situations with competing priorities.

Desirable qualifications

• Scripting ability for automation, log parsing, or workflow improvement (Python, Bash, or similar) — you don't need to be a software engineer, but you can write a script when it saves you an hour.
• Deep familiarity with MITRE ATT&CK as an operational tool for detection gap analysis and threat hunting hypothesis development.
• Experience with AWS security telemetry (CloudTrail, GuardDuty, Security Hub) and integrating cloud signals into a corporate SIEM.
• Familiarity with Zero Trust and identity-centric security models as they apply to policy enforcement in IAM and endpoint platforms.
• Platform-specific certifications such as CrowdStrike Certified Falcon Administrator, Splunk Core Certified Power User, or equivalent — or practitioner certifications like GCIH, GCIA, GCFE, or GCFA.

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.

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 

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

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

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

Meet the team:

At Latitude, the Overwatch team builds the systems that run and manage large amounts of computing work across the organization. This work helps engineers train models, test software, and move data reliably at scale. The team owns the platforms that schedule and monitor long-running jobs and keep shared computing resources running efficiently. In addition, the team develops systems that deliver software and data to vehicles and collect logs and telemetry from real-world driving.

What you’ll do: 

• Build and improve systems that orchestrate, schedule, run, and monitor large numbers of ML jobs used across the company for training automated driving features
• Design reliable software that handles failures, retries, and high load while keeping results accurate and timely
• Build and maintain backend services and APIs that support job submission and reliable execution of long-running work
• Investigate production issues, identify root causes, and implement fixes that prevent repeat failures
• Review designs and code to ensure solutions are simple, reliable, and scalable over time
• Collaborate closely with infrastructure, machine learning and data science teams to ensure computing systems are reliable and being optimally used
• Build with scale and maintainability in mind, while rapidly iterating on new ideas

What you'll need to succeed:

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 4+ years of relevant experience (or Master's degree and 2+ years of relevant experience, or PhD)
• Experience in designing high-scale distributed systems that meet user requirements
• Prior experience building or operating large-scale job scheduling or workload orchestration platforms, such as container-based or batch computing systems used to manage shared compute resources
• Expertise in back-end languages (e.g., Kotlin, Java, Go, Python) and frameworks
• Experience designing and building distributed systems using modern backend patterns for reliability, coordination, and asynchronous processing
• At least 6+ years of experience in a related field where actively coding & designing 80% of the time
• Comfort working in a fast-moving environment with evolving requirements, where ideas are tested quickly and real user impact guides decisions

Nice to have: 

• Exposure to performance tuning, cost optimization, or capacity planning for compute-intensive workloads
• Experience working on large-scale computing platforms that manage shared resources and competing workloads

What we offer you:

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

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

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

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

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

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

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

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

Meet the team:

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

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

What you’ll do: 

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

What you'll need to succeed:

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

Nice to have: 

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

What we offer you:

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

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

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

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

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

The Team

This role can sit in our NYC HQ on a hybrid basis, or it can be fully remote while working from a location based in either Eastern or Central time zones. We are looking for an experienced Senior Engineer for our SRE, Atlas team to support, maintain and grow the Atlas platform. As a senior SRE, you will be expected to be able to design & build complex systems, operate with autonomy and act as owner for everything you do. 

The SRE Atlas team works alongside the various Atlas software engineering teams to provide expertise about running systems at scale, build new tooling and automation and perform essential maintenance of the Atlas fleet. 

This is an SRE team, which means you can expect a highly hands-on approach, tackling the technical challenges of implementing large scale solutions that have the ability to impact our customer’s most crucial workloads. 

Role Overview

We are seeking a talented Site Reliability Engineer (SRE) with a strong infrastructure background. This role requires engineers to have a customer-first mindset to ensure that everything we do results in a stronger product and a better experience for all Atlas customers. 

The ideal candidate should

• Have 5+ years of experience running critical systems at scale
• Value efficiency in processes and operations, and display a preference for automation over manual processes (“allergic to ops work”)
• Be familiar with a major cloud provider (AWS, Azure, or GCP) and possess the ability to build and operate systems in a multi-cloud environment
• A strong understanding of how to run a large scale Linux environment, including low level fundamentals 
• Firm grasp of at least one modern programming language, beyond basic scripting (Go, Ruby, Python)
• Solid understanding of web and network protocols and standards (HTTP, TLS, DNS, etc)

Special Requirements:

• Be a US Citizen

Expectations

• Participate in the development of a reliable and resilient multi-cloud platform that hosts business critical applications for a wide & varied range of customer applications
• Collaborate with service-owning teams to provide internal support, solve technical challenges and adapt or build tooling to solve novel use cases in a generic fashion
• Participate in a 24/7 on-call rotation to swiftly resolve issues related to any disruption of our customer facing Atlas fleet, ensuring minimal disruption and high availability

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions 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.

Req ID: 426187

MongoDB’s Storage Layer Services (SLS) team is re-architecting the MongoDB cloud storage layer and sits at the heart of our next-generation cloud storage architecture. This relatively new team is building performant, multi-tenant distributed storage services that both enhance today’s Atlas storage stack and enable more customer workloads to run more efficiently.

You will partner with the teams building these storage services to define SLOs, shape capacity plans, and ensure the reliability, durability, and operational safety of the storage layer that underpins Atlas. You’ll join a small, senior team of SREs as founding members of this organization, playing a crucial role in executing on a multi-year roadmap for MongoDB’s cloud storage architecture.

This role can be based out of our Boston, New York City, Raleigh, Miami, Pittsburgh or remotely in the United States while physically based in an Eastern or Central time zone location. 

The ideal candidate should

• Have 6+ years of experience working on software development and operating distributed systems
• Proficiency in Python, Go, or a similar language
• Have operated or supported stateful storage or database systems at scale, and are comfortable with durability, consistency, and recovery trade-offs.
• Possess a customer-focused mindset
• Value efficiency in processes and operations
• Prefer automation over manual processes. We are a small team of software engineers with a strong bias towards software solutions to avoid toil
• Experience using and extending containerization technologies, particularly Kubernetes, to enhance application agility, optimize resource utilization, and accelerate time-to-market
• Expertise in cloud infrastructure platforms, including AWS, Google Cloud Platform (GCP), or Azure
• Understanding of Linux operating system internals and networking concepts (e.g., TCP/IP, DNS, TLS, routing)

Responsibilities 

• Work on our multi-tenant distributed storage systems, balancing long-term strategic infrastructure goals with immediate engineering needs
• Build for reliability, making services and infrastructure available, resilient, fault-tolerant, and self-healing
• Identify and configure key metrics to detect incidents and quantify service health, availability, and performance
• Participate in a 24/7 on-call rotation to resolve issues involving the storage infrastructure
• Become an expert in infrastructure performance, helping us optimize from the application level all the way to the kernel

Strong candidates may also have experience with:

• Leading major architectural shifts, such as moving from legacy storage stacks to new multi-tenant storage architectures, including planning and executing large-scale data and workload migrations with tight availability and durability requirements
• Managing and scaling infrastructure across multi-cloud environments (AWS, GCP, or Azure)
• Designing secure, multi-tenant runtime environments at scale

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform, the most widely available, globally distributed database on the market, helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and over 60,000 customers, including 75% of the Fortune 100 and AI-native startups, relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB, Inc. provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type and makes all hiring decisions 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.

Req ID: 1273396252

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 Client Platform Engineer to join our Enterprise Site Reliability (SRE) team to lead the management of our enterprise Windows, Mac, and Ubuntu clients. The team is responsible for designing, implementing, and maintaining scalable and secure client device infrastructure. They also automate device deployment, configuration, and management processes.

This role will contribute to delivering the benefits of self-driving by leading the development of tailored client device solutions that address Aurora-wide and team-specific requirements for software and hardware development and manufacturing.

In this role you will

• Guide the approach and execution of the Client Platform Engineering Team
• Plan, design, and implement scalable solutions to manage Aurora's physical and virtual client platforms (Macs, Windows, Ubuntu) to ensure they receive security patches, configuration, and software package updates
• Partner with IT Support, InfoSec, and Developer Experience on strategy and implementation of client platform management solutions
• Handle escalations from IT Support, with an emphasis on mentoring and empowering IT Support to address similar problems
• Participate in the Enterprise SRE 24/7 on-call rotation

Required qualifications

• Experience of at least 8 years in Client Platform engineering and at least 3 years in leading engineering solutions (design to implementation) at scale.
• Expertise with client device lifecycle management, including experience across multiple client operating systems and various hardware platforms.
• Experience with MacOS, Windows, and Linux system administration.
• Experience deploying configuration management tools such as Intune, Kandji, Puppet, Ansible, or Chef.
• Experience with automation and tool development, preferably using Powershell, Go, or Python.
• Strong change management skills, including rollout planning and communication, and collaborating with stakeholders.
• Understanding of client endpoint security concepts and experience applying security hardening to client devices, such as CIS Benchmarks.
• Outstanding written and verbal communication skills that drive executional impact at scale. 
• Experience with automating testing for imaging, provisioning, and configuration management.

Desirable qualifications

• Experience working within cloud environments such as AWS, GCP, or Azure.
• Experience in environments deploying containerized workflows, using tools such as Docker or Kubernetes.
• Familiarity with SRE concepts such as SLIs, SLOs, SLAs, incident response, and best practices and partnering with teams on them.
• Experience with Infrastructure as Code (IaC) tools such as Terraform, Pulumi, or CloudFormation

The base salary range for this position is  $163,000 - $236,500 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.

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

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

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

Meet the team:

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

What you’ll do: 

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

What you'll need to succeed:

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

Nice to have: 

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

What we offer you:

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

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

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

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

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

Company Name: Hellbender Inc.

Job Title: Robotics Engineering Internship

Department: Engineering

Report to: Engineering Manager 

Who we are:

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

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

Job Summary: 

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

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

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

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

Essential Duties and Responsibilities:

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

Work Location: UPARC Pittsburgh

Opportunity for advancement: 

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

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

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

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

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

Mission Summary:

Motional’s onboard autonomous driving system team works at the intersection of software engineering, machine learning, sensors, and hardware compute platforms to evolve Motional’s next-generation on-board autonomous driving system. As part of this team, the High Performance Compute Platform team is responsible for Motional’s current and next-generation onboard autonomous driving system. If you are a software engineer and love the idea of working on embedded AI hardware and software compute systems to create the next generation of autonomous vehicles, we would love to talk with you. We are hiring in a range of levels, from graduate engineers to Staff engineers.

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

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

THE ROLE:

Are you passionate about driving innovation in the data storage industry? Are you skilled in crafting technical solutions that exceed customer expectations? If so, we have an exciting opportunity for you! Everpure (formerly Pure Storage), a leader in the data storage and flash technology space, is seeking a talented and motivated Senior Pre-Sales Systems Engineer to join our dynamic team. 

As a Senior Pre-Sales Systems Engineer, you will play a crucial role in understanding our customers' unique challenges and tailoring Everpure solutions to meet their specific needs. Collaborating closely with the sales team, you will act as a technical expert during the sales process, helping to showcase the value of our products and services.

WHAT YOU’LL DO:

• Develop an exhaustive understanding of what drives a customer’s business and what motivates their decision making
• Connect the dots from technology solutions, inclusive of the Everpure portfolio and others from the ecosystem, to measurable customer business outcomes
• Partner closely with account managers, specialists and channel partners to create a seamless and holistic customer experience and strategy to drive revenue growth and net new business
• Delight customers and teammates with your technical leadership and domain expertise on storage products, distributed storage architectures, file systems, and competitive storage offerings in the DAS, NAS and SAN product spaces
• Take control of evaluations,  benchmarks and system configurations
• Build and deliver technical product and architecture presentations with vigor to customers and lock in the technical win with clients and prospective accounts
• Capture requirements and translate Customer’s business needs into innovative solutions to accelerate their growth and capacity
• Seek out and spur new opportunities for interoperability, functional, and performance testing/validation
• Promote mutual roadmap and planning exchanges
• Liaise with product and technical marketing to produce materials (i.e. whitepaper, web presentations) that support overall alliance plans and objectives
• Stay current with the competition and ensure that materials accurately reflect the latest, differentiated solution positioning
• Move with market trends and competitive landscape to promote thought leadership within our organization
• Lead by example living the Everpure Values:  Persistence, Creativity, Teamwork, Ownership and Customer-first  

WHAT YOU BRING:

• Pre-sales experience is required
• 5 or more years of relevant experience, mixed among technology, design, and communications required. Experience supporting the sales of enterprise storage, networking, systems, cloud, or software to enterprise accounts preferred
• Deep understanding of the architecture, design and implementation of multi-tiered client/server and web-based computing solutions
• Must have a familiarity with modern web architecture a plus (LAMP stack, scale-out vs scale-up architectures, AWS well-architected framework, microservices architecture)
• Prior experience in targeting new prospects and converting them into clients
• Contribute significant portions and/or lead responses to RFPs, RFQs and RFIs
• Superior knowledge of current and emerging storage architectures (FC, iSCSI, NAS, OSD, SAN)
• Previous experience with Linux, NFS file systems and Linux distributed network environment
• Installation/configuration of distributed computing, multiprocessing, virtual memory subsystem, storage subsystems architecture, shared memory architectures, cache architectures, windowing systems
• Strong knowledge of digital transformation to a Cloud Native architecture, On-Prem, Public Cloud, Provisioning Automation, and Containers
• Knowledge of VMware, Local Area Networking, Ethernet, TCP/IP and general networking
• Familiarity with AWS, Azure, GCP, containers, k8s and microservices architectures a plus
• Curiosity and passion around technology and explaining and showing new technology platforms and concepts to customers
• Familiarity with storage-intensive applications and their requirements such as structured databases (SQL, Oracle) is highly desirable
• Excellent verbal and written interpersonal skills

#LI-REMOTE

#LI-JL4

About the Role

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

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

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

About the Work

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

About You

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

You Might Also Have

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

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

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

Mission Summary:

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

What you'll be doing:

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

What we're looking for:

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

Bonus points (not required):

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

Mission Summary:

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

What you'll be doing:

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

What we're looking for:

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

Bonus points (not required):

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

Mission Summary:

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

What you'll be doing:

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

What we're looking for:

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

Bonus points (not required):

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

Required:

• 3+ in Windows desktop application development using Windows App SDK, WinUI (or similar), C#, XAML — and ideally additional experience with native Windows code (C++, Win32/WinRT/COM).
• Deep understanding of Windows application architecture, including interop between managed code (.NET) and native code.
• Proven track record of designing, building, and shipping production-quality desktop applications, with an emphasis on reliability, performance, scalability, and maintainability.
• Strong experience with accessibility APIs on Windows (e.g. Microsoft UI Automation or similar), and a dedication to building accessible and inclusive software.
• Excellent software engineering fundamentals: OOP, design patterns, data structures, algorithms, memory management, multi-threading or asynchronous programming (where relevant).
• Experience leading technical design, mentoring other engineers, conducting code reviews, and making architecture-level decisions.
• Strong communication skills; ability to articulate tradeoffs, collaborate with cross-functional teams, and drive consensus.
• A user-centric mindset: focus on building polished, intuitive, and accessible experiences for end users.

Preferred / Bonus:

• Experience with writing automated tests for UI — unit tests, integration tests, UI automation tests; familiarity with relevant testing frameworks.
• Experience with performance optimization for desktop apps (memory usage, startup time, rendering performance, high-DPI support, responsiveness under load).
• Experience with localization/globalization, right-to-left UI support, internationalization, accessibility for multiple regions.
• Familiarity with telemetry, analytics, crash reporting, logging, and error monitoring in desktop applications.
• Previous experience in shaping CI/CD workflows, release pipelines, and deployment strategies for desktop applications.
• Demonstrated ability to take ownership of feature areas or modules and drive them long-term, including maintenance, refactoring, and technical debt management.

What we offer

• A high-impact role: you will define architecture, shape the future of our Windows product, and directly influence what millions of users see and experience.
• A collaborative, flat-structure engineering culture — you are not just a coder, but a builder and a decision-maker.
• Opportunities to lead — mentor others, steer technical direction, and grow into broader technical leadership (e.g. Tech Lead, Architect).
• Flexibility, autonomy, and responsibility: you define how to solve problems, own features end-to-end, and contribute to long-term product vision.
• A purpose-driven mission: building software that’s reliable, accessible, and user-centered — making a real difference for people.

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience             

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 
Refer them! 

Speechify is committed to a diverse and inclusive workplace. 
Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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

Mission Summary:

Our Vehicle Platform Components team is seeking a highly motivated Senior Engineer to assume ownership of the development and integration of the autonomous vehicle Electronic Controllers (ECUs) and Data Loggers. This position serves as the primary technical owner for the development, validation, and production readiness of our ECUs. The incumbent will ensure that components adhere to all functional requirements and quality standards, and will support component delivery to satisfy all performance, cost, and timing objectives.

Key Responsibilities:

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

What We’re Looking For:

• 7+ years of experience in automotive component design, development and integration.
• Bachelor’s or Master’s degree in Electrical Engineering, Electronics Technology or a related field.
• Demonstrated expertise in the design, development, and integration of complex Electronic Control Units (ECUs).
• Proven experience utilizing widely adopted Microcontrollers (MCUs) and Systems-on-Chips (SoCs) within automotive ECU applications.
• Experience with automotive communication protocols, including CAN, CAN-FD, and Automotive Ethernet (10GBASE-T1).
• Experience with high-bandwidth data acquisition systems, including proficiency in PCIe switching and direct storage technologies.
• Familiarity with NVIDIA DRIVE AGX Orin / Thor architecture and developer kits.
• Proficiency in Linux, including the ability to develop scripts (e.g., Python, C++, bash) for testing and validation, and layer 2 networking concepts.
• Experience with lab equipment, including power supplies, oscilloscopes, multimeters, and function generators.
• Proficiency in automotive diagnostic tools, including Vector tools (CANoe, CANape, vFlash) and DoCAN/DoIP.
• Experience with automotive environmental, EMI, and shock/vibration testing.
• Experience in root-cause analysis, with a focus on utilizing AV / ADAS vehicle logs to pinpoint scenarios that negatively affect autonomous system performance.
• Familiarity with automotive components validation documentation and procedures, such as DVP&R, DFMEA and PFMEA.
• Experience with requirement compliance, issue-tracking and task management software platforms such as JIRA, Polarion, Confluence, etc.
• Demonstrated experience collaborating with an automotive Tier-1 supplier on the technical development of electronic components.
• Understanding of vehicle integration, packaging, and functional safety standards (ISO 26262)
  
  

Bonus Points:

• Prior experience in an autonomous vehicle or robotics company.
• Prior experience of ECU design for autonomous vehicles.
  
  

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

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!

At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. 

Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.

About the role...

As a Platform Engineer on the Compute team, you’ll improve how engineers build and run services, helping ensure our compute platform is reliable at scale for our learners and fellow Duo engineers.

The Compute team builds and operates the core compute platform that powers our applications. We build paved roads (self-service platform primitives, templates, and tooling) and we operate them so product engineers can focus on shipping features with confidence.

This role is based in our Pittsburgh office and requires in-office presence Monday through Thursday.

🧠  You will...

• Build and operate core compute primitives that power production workloads based on Kubernetes, across different regions and cloud providers. 
• Improve the delivery pipeline from commit to production by evolving our GitOps and deployment patterns, making rollouts safer and faster.
• Raise the operational bar: define SLOs, build dashboards/alerts, write runbooks, and participate in on-call/incident response to keep the platform dependable.
• Enable effective self-service by turning platform capabilities into reusable abstractions.

✅  You have...

• Strong problem-solving skills and experience delivering and shipping pragmatic solutions in production environments.
• Experience with distributed systems fundamentals (networking, service-to-service communication, failure modes, caching/storage concepts).
• Experience working on production systems (through industry roles, internships, or substantial open-source work).
• Experience with one or more CI/CD tools (Jenkins, Argo CD, GitHub Actions) and infrastructure management tools (Terraform, CloudFormation)
• Clear written and verbal communication skills—comfortable writing docs/runbooks and collaborating across teams.
• Functional knowledge of Linux system administration and automation
  
  
  

⭐  Exceptional candidates will have...

• A Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience
• Experience managing a production infrastructure on AWS, Google Cloud, Alibaba Cloud, or Azure.
• Exposure to multi-cluster or multi-region architectures and the operational patterns that make them reliable.
• Experience with service mesh / zero-trust networking patterns (e.g., Istio mTLS, traffic management, authorization policies).

Our mission at Duolingo is to develop the best education in the world and make it universally available. It’s a big mission, and that’s where you come in!

At Duolingo, you’ll join a team that cares about finding innovative solutions to complex technical problems, running countless experiments (300+ at a time!) with our massive user base to make data-driven decisions, and educating our users and employees alike. You’ll have limitless learning opportunities, mentorship and collaboration with world-class minds, and a variety of projects with large scopes — while doing work that’s both fun and meaningful. 

Join our life-changing mission to develop education for our half a billion (and growing!) learners around the world.

About the role...

As a Platform Engineer on the Compute team, you’ll improve how engineers build and run services, helping ensure our compute platform is reliable at scale for our learners and fellow Duo engineers.

The Compute team builds and operates the core compute platform that powers our applications. We build paved roads (self-service platform primitives, templates, and tooling) and we operate them so product engineers can focus on shipping features with confidence.

This role is based in our Pittsburgh office and requires in-office presence Monday through Thursday.

🧠  You will...

• Build and operate core compute primitives that power production workloads based on Kubernetes, across different regions and cloud providers. 
• Improve the delivery pipeline from commit to production by evolving our GitOps and deployment patterns, making rollouts safer and faster.
• Raise the operational bar: define SLOs, build dashboards/alerts, write runbooks, and participate in on-call/incident response to keep the platform dependable.
• Enable effective self-service by turning platform capabilities into reusable abstractions.

✅  You have...

• Strong problem-solving skills and experience delivering and shipping pragmatic solutions in production environments.
• Experience with distributed systems fundamentals (networking, service-to-service communication, failure modes, caching/storage concepts).
• Experience working on production systems (through industry roles, internships, or substantial open-source work).
• Experience with one or more CI/CD tools (Jenkins, Argo CD, GitHub Actions) and infrastructure management tools (Terraform, CloudFormation)
• Clear written and verbal communication skills—comfortable writing docs/runbooks and collaborating across teams.
• Functional knowledge of Linux system administration and automation
  
  
  

⭐  Exceptional candidates will have...

• A Bachelor’s degree in Computer Science, related technical field, or equivalent practical experience
• Experience managing a production infrastructure on AWS, Google Cloud, Alibaba Cloud, or Azure.
• Exposure to multi-cluster or multi-region architectures and the operational patterns that make them reliable.
• Experience with service mesh / zero-trust networking patterns (e.g., Istio mTLS, traffic management, authorization policies).

Mission

Speechify is the easiest way to listen to the world’s information. Articles on the web, documents in the cloud, books on your phone. We absorb it all and let you listen to it at your desk, on the go, at your own speed, and with tools that make learning easier, deeper, and faster.

What streaming services have done for audio entertainment, we’re doing for audio information. And whatever we’re doing seems to be working. We’re #1 in our category, and experiencing exponential growth.

Overview

We're looking for a Senior Software Engineer to join our Core Experiences Team. This team builds and maintains the foundational services and SDKs that power Speechify’s product experience across platforms. It's a critical role for someone who enjoys working at the intersection of product and infrastructure, thinks strategically, and is passionate about designing clear, reliable APIs and simple systems that directly enhance the user experience.

What You’ll Do

• Collaborate with Speechify’s Product Teams to scope projects, find ways to reduce scope to get faster feedback from customers, navigate the integration/UX tradeoffs relevant to different product teams, and deliver solutions via our cross-platform SDK
• Optimize existing functionality to ship things like faster loading and more intelligent parsing by designing more efficient abstractions and improving our algorithms
• Ship cloud functions, lightweight backend services, and jobs using Kotlin

An Ideal Candidate Should Have

• Systems thinking. You know that optimizing a system requires end-to-end design, and you believe simplicity is valuable.
• Speed. You work quickly to generate ideas and options and know how to decide which things can ship now and what things need time
• Focus. We’re a high-growth startup with a busy, remote team. You know how and when to engage or be heads down
• Collaboration. You know how to inspire, play, and negotiate with opinionated designers, marketers, and PMs
• Preferred Tech Stack:
  • Kotlin Multiplatform (Java experience is OK but role is Kotlin Multiplatform) 
  • Prior experience with GCP is a plus

What We Offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest growing sectors of tech, the intersection of artificial intelligence and audio.

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

The mission of Speechify is to make sure that reading is never a barrier to learning.

Over 50 million people use Speechify’s text-to-speech products to turn whatever they’re reading – PDFs, books, Google Docs, news articles, websites – into audio, so they can read faster, read more, and remember more. Speechify’s text-to-speech reading products include its iOS app, Android App, Mac App, Chrome Extension, and Web App. Google recently named Speechify the Chrome Extension of the Year and Apple named Speechify its 2025 Design Award winner for Inclusivity.  

Today, nearly 200 people around the globe work on Speechify in a 100% distributed setting – Speechify has no office. These include frontend and backend engineers, AI research scientists, and others from Amazon, Microsoft, and Google, leading PhD programs like Stanford, high growth startups like Stripe, Vercel, Bolt, and many founders of their own companies.

Overview

The responsibilities of our Platform team include building and maintaining all backend services, including, but not limited to, payments, analytics, subscriptions, new products, text to speech, and external APIs.

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, is passionate about making product decisions, and has experience building great user experiences that delight users.

We are a flat organization that allows anyone to become a leader by showing excellent technical skills and delivering results consistently and fast. Work ethic, solid communication skills, and obsession with winning are paramount. 

Our interview process involves several technical interviews and we aim to complete them within 1 week. 

What You’ll Do

• Design, develop, and maintain robust APIs including public TTS API, internal APIs like Payment, Subscription, Auth and Consumption Tracking, ensuring they meet business and scalability requirements
• Oversee the full backend API landscape, enhancing and optimizing for performance and maintainability
• Collaborate on B2B solutions, focusing on customization and integration needs for enterprise clients
• Work closely with cross-functional teams to align backend architecture with overall product strategy and user experience

An Ideal Candidate Should Have

• Proven experience in backend development: TS/Node (required)
• Direct experience with GCP and knowledge of AWS, Azure, or other cloud providers
• Efficiency in ideation and implementation, prioritizing tasks based on urgency and impact
• Preferred: Experience with Docker and containerized deployments
• Preferred: Proficiency in deploying high availability applications on Kubernetes

What We Offer

• A dynamic environment where your contributions shape the company and its products
• A team that values innovation, intuition, and drive
• Autonomy, fostering focus and creativity
• The opportunity to have a significant impact in a revolutionary industry
• Competitive compensation, a welcoming atmosphere, and a commitment to an exceptional asynchronous work culture
• The privilege of working on a product that changes lives, particularly for those with learning differences like dyslexia, ADD, and more
• An active role at the intersection of artificial intelligence and audio – a rapidly evolving tech domain

The United States Based Salary range for this role is: 140,000-200,000 USD/Year + Bonus + Stock depending on experience

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

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

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

Key Responsibilities 

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

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

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

Required Qualifications & Experience

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

Desired Qualifications & Experience Requirements 

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

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

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

Mission Summary:

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

Key Responsibilities:

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

What We’re Looking For:

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

Bonus Points:

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

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

The work environment characteristics described here represent those a team member encounters while performing the essential functions of this job. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. The team member is regularly exposed to mechanical and computer parts. The team member is occasionally exposed to fumes and/or airborne particlesThe noise level in the environment is low to moderate.

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

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

Mission Summary:

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

What You’ll Be Doing:

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

What We’re Looking For:

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

Bonus Points:

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

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

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

Mission Summary:

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

What You’ll Be Doing:

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

What We’re Looking For:

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

Bonus Points:

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

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

Mission Summary:

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

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

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

What you'll do:

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

What you'll be working on:

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

What you bring:

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

Bonus points for experience with:

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

Mission Summary:

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

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

What you'll be doing:

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

What we're looking for:

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

Mission Summary:

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

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

What you'll be doing:

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

What we're looking for:

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

Mission Summary:

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

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

What you'll be doing:

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

What we're looking for:

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

Mission Summary:

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

What you’ll be doing:

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

What we’re looking for:

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

Bonus Points (not required):

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

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

Mission Summary

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

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

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

What you'll be doing:

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

What we're looking for:

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

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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.