This position is looking for a highly motivated flight test engineer, and test lead with emphasis in developmental test of a new and revolutionary Group 5 UAS. You will work heavily with the program leadership and a wide spectrum of cross-departments to help build a team focused on solving hard problems and changing the industry forever. The role will be responsible for assisting on planning, coordination, execution and reporting on all facets of the test program.

The Test and Evaluation team at Anduril works across the entire spectrum of products and business lines, as well as all flight operations and test range management. Our team conducts full system level development testing, new production acceptance testing, sub-component qualification testing and much more. In short, if it involves test, we support it. If you are interested in working in an extremely innovative and fast paced environment, where your work directly makes an impact and difference in the products that are fielded this a fantastic opportunity.

WHAT YOU’LL DO

• As a lead Flight Test Engineer, under minimal supervision, you will determine, develop and recommend various approaches to achieve T&E goals set by Anduril T&E and Program leadership. You will manage, guide, and execute technical efforts of the Fury development test program. You will provide direct input to test event planning, preparation, execution and reporting.
• This position will focus heavily on new aircraft development, with emphasis on envelope expansion, flying qualities, vehicle autonomy, and test in operational environments.
• You will be responsible for ensuring comprehensive flight test campaign execution of multiple test articles in support of high-risk test events.
• Test duties include the testing hardware and software in laboratory, ground and flight test environments, with emphasis placed on resource planning. You will be expected to seek process improvements to increase test efficiency across all test environments.
• You will be directly responsible for supporting test execution at government test facilities with USG partners.
• You will facilitate and lead the technical interactions between disparate engineering teams. You will coordinate across the members of T&E IPT, including Flight Operations and Maintenance.
• You will directly contribute to periodic and milestone engineering reviews, often facilitating technical discussions between Anduril and customer representatives.
• Faced with numerous technical and execution challenges, you will be expected to develop creative solutions to unique problems. You will be biased for action — you are empowered to engage your team to solve and fix any problem you encounter without direct supervision.
• You will be part of an organization that challenges traditional T&E paradigms and is poised to affect the trajectory of the flight test industry.

REQUIRED QUALIFICATIONS

• 10+ years of experience as test conductor/director for developmental aircraft, weapons, or missile systems.
• A bachelor's degree or a related technical discipline from an accredited institution. May substitute equivalent engineering experience in lieu of education.
• Test engineering experience working with developmental systems of manned and/or unmanned aircraft to include requirements development, test planning and execution, and test reporting.
• Must have a complete understanding of Test & Evaluation engineering concepts, principles, codes, and theory; with experience demonstrating a broad application of those areas. This includes experience working across program Integrated Product Teams to influence system design or configuration.
• Previous experience with and current working knowledge of DCMA INST 8210, MIL-STD-516, 14 CFR, and service related T&E guiding documents. Foundational expertise and working knowledge of the National Airspace System, government restricted airspace and UAS operating rules and regulations thereof.
• Prior experience conducting development flight test operations at military ranges.
• Must possess the ability to understand new concepts quickly; apply them accurately; organize, schedule, and coordinate work phases; and determine the appropriate approach at the task level or, with assistance, at the project level to provide solutions to a range of complex problems.
• Strong computer and documentation experience.
• Must have strong communication (written and verbal) and interpersonal skills.
• Ability to work independently and as part of a team; able to perform complex tasks in one or more engineering areas.
• Experience with large aircraft development and working with the Department of Defense (DoD)
• Able to work extended hours as required.
• Ability to travel as required for test planning and execution
• Ability to immediately obtain a U.S. Top Secret-Level security clearance.

PREFERRED QUALIFICATIONS

• 15+ years experience in Test & Evaluation, or related technical fields.
• Previously held a role as the Flight Test Engineering Lead
• Been a part of the first flight of a developmental aircraft, or major aircraft system.
• Bias for action – if you see a problem, you want to solve and fix it
• Experience managing individuals or teams of multiple individuals
• Experience with large UAS development
• Previous experience working within a Combined Test Force or equivalent

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.

At Anduril we are developing unmanned aerial systems capable of terminal guidance, long range intelligence collection, precision relative and global navigation, and unsupervised autonomy. The Test and Evaluation team works across the entire spectrum of products ranging from Lattice Ghost UAS, Sentry Tower, cUAS, missile, Fury and many of our other platforms.

As a Group 5 Test Pilot, you will support the development and field testing of Anduril’s largest and most powerful Unmanned Aerial System products. In this role, you will prepare aircraft for flight, conduct flight tests as the test pilot, and support the test engineering team throughout the lifecycle of the developmental aircraft.

WHAT YOU’LL DO

• Collaborate closely with Flight Test Engineers and Discipline Engineers to develop safe, effective, and efficient test procedures, evaluate system and test safety, and verify the functional design of the system.
• Participate in ground and flight testing of developmental aircraft to determine compliance with specifications, validate airworthiness, and assess operational suitability.
• Assist in developing system test procedures and engage in laboratory and surrogate open-air environment testing.
• Serve as a guiding member within the Test and Evaluation team, regularly interfacing with the T&E lead, T&E Technical Director, Chief Test Pilot, Lead Flight Test Engineer, and customer representatives.
• Take direct responsibility for the safe flight of the aircraft and act as an advisor during safety reviews, design reviews, and airworthiness reviews.
• Expand the mission envelope by pushing the boundaries of safe and normal flight.
• Support Fury flight tests as a surrogate and chase pilot, flying high-performance jet aircraft in demanding roles including photo/video, air data pacer, and safety chase across the flight envelope.
• Participate in flight operations and help direct the flight test program.
• Collaborate with other test pilots to approve control station configurations, author flight procedures, develop and verify emergency procedures, and support test team and control room training.
• Review test procedures, flight test plans, flight test cards, operating limitations, flight test schedules, support documents, and ground handling documents in preparation for ground and flight testing.
• Attend system design and configuration control meetings, providing input to resolve change requests and determining change priority, timelines, and test verification requirements leading up to software releases and aircraft block changes.
• Develop creative solutions to technical and execution challenges, acting with a bias for action and engaging your team to solve problems efficiently.

REQUIRED QUALIFICATIONS

• Graduate of a U.S. military test pilot school (TPS) or meet DCMAINST 8210.1 series alternate education and experience qualifications for contractor UA pilot/operator.
• 5+ years experience as a Group 5 UAV pilot.
• 2,000 hours Pilot-in-Command time or 500 hours in unmanned aircraft.
• Qualifying hours must include 200 hours Pilot-in-Command during engineering flight test and 10 hours during experimental flight test.
• Commercial pilot certificate with instrument rating.
• FAA Class 2 Medical, renewed annually.
• One of the following education and experience combinations:
• Undergraduate or higher degree in aerospace-related engineering or scientific discipline plus one year of applicable engineering test flight experience.
• Undergraduate or higher degree in other engineering or scientific discipline plus two years of applicable engineering test flight experience.
• Non-engineering undergraduate or higher degree plus three years of applicable engineering test flight experience.
• No degree plus four years of applicable engineering test flight experience.
• Ability to travel as required to support off-site aircraft testing.
• Strong ability to quickly understand new concepts, apply them accurately, organize, schedule, and coordinate work phases, and determine appropriate approaches to complex problems.
• Excellent written and verbal communication and interpersonal skills, especially regarding technical subjects and authoring technical documents supporting safe aircraft operation.
• Experience authoring flight manuals and technical documentation necessary to operate developmental aircraft and delivering configuration-controlled publications to customers.
• Proficiency with basic MS Office tools (Word, PowerPoint, Excel).
• Ability to work independently and as part of a team; capable of performing complex tasks.
• Willingness to work extended and irregular hours.
• Ability to obtain and maintain a U.S. TS/SCI security clearance.

PREFERRED QUALIFICATIONS

• 10+ years experience as a Group 5 UAV pilot working with developmental aircraft.
• 2,000 hours Pilot-in-Command time or 500 hours in unmanned aircraft.
• ATP certificate with Class 1 medical.
• Certified Flight Instructor / Instrument.

About the Role

The Revenue Operations team at Gusto is a full-stack team responsible for data, analytics, and operational excellence in pursuit of scaling our revenue growth. The Go-To-Market Analytics team is one functional area, responsible for defining and owning the metrics for scaling our Sales teams. 

Gusto is looking for a Revenue Analytics Engineer to build and maintain foundational data infrastructure that is crucial to growing and scaling our Sales efforts. In this role, you will partner with our GTM analysts to scope and deliver data products for an audience ranging from company and revenue leadership to operational and frontline sales. In doing so, you will own significant portions of our sales data from end-to-end, focusing on the transformation, design, and visualization workflows. In addition, you will establish best practices for systems design and workflows to maximize usefulness of AI at scale. 

This role will report to the Head of Go-To-Market analytics, and partner closely with Data Science, Data Platform, and Business Technology teams. 

Here’s what you’ll do day-to-day:

• Establish relationships with internal stakeholders to determine business needs, scoping and delivering solutions through data products
• Design, build, and maintain data pipelines and dashboards to automate “keep the lights on” work out of manually-managed processes
• Build a data foundation by incorporating business logic into raw data tables, laying the groundwork to enable value-add insights
• Create a dynamic reporting environment based on stakeholder needs
• Identify data discrepancies and set best practices for data logic to create a clean and well-documented environment
• Collaborate with broader data organization as steward to the definition and process management of core Gusto metrics

Here’s what we're looking for:

• Education or work experience in Engineering or Computer Science, or a related technical field 
• 7+ years of experience in an analytics engineering, business intelligence, or technical data analytics role
• Experience with SQL and ETL optimization techniques, especially within cloud-based data warehouses like Redshift, Snowflake, etc.
• Command-line experience and familiarity with version control collaboration tools (git)
• Experience with data pipeline management technologies with dependency checking, such as Airflow, as well as schema design and data modeling tools (dbt)
• Experience with data visualization technologies, e.g., Tableau, Looker, Sigma, Mode, Hex
• Experience with Python and data ingestion tools
• Ability to problem-solve open-ended problems and project manage dependencies and timelines to optimal outcomes
• Ability to demonstrate tools, business intuition, and attention to detail for data validation and QA 

Our cash compensation amount for this role is targeted at $138,000-156,000 in Denver & most remote locations, and $168,000-189,000 in New York & San Francisco Bay Area. Stock equity is additional. Final offer amounts are determined by multiple factors including candidate experience and expertise and may vary from the amounts listed above.

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

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

We're looking to hire for our Data side of our AI team at Speechify. This role is responsible for all aspects of data collection to support our model training operations. We are able to build high-quality datasets at petabyte-scale and low cost through a tight integration of infrastructure, engineering, and research work. We are looking for a skilled Software Engineer to join us.

What You’ll Do

• Be scrappy to find new sources of audio data and bring it into our ingestion pipeline
• Operate and extend the cloud infrastructure for our ingestion pipeline, currently running on GCP and managed with Terraform.
• Collaborate closely with our Scientists to shift the cost/throughput/quality frontier, delivering richer data at bigger scale and lower cost to power our next-generation models.
• Collaborate with others on the AI Team and Speechify Leadership to craft the AI Team’s dataset roadmap to power Speechify’s next-generation consumer and enterprise products.

An Ideal Candidate Should Have

• BS/MS/PhD in Computer Science or a related field.
• 5+ years of industry experience in software development.
• Proficiency with bash/Python scripting in Linux environments
• Proficiency in Docker and Infrastructure-as-Code concepts and professional experience with at least one major Cloud Provider (we use GCP)
• Experience with web crawlers, large-scale data processing workflows is a plus
• Ability to handle multiple tasks and adapt to changing priorities.
• Strong communication skills, both written and verbal.

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.

Compensation: The United States base salary range for this full-time position is $140,000-$200,000 + bonus + equity 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.

Mission Summary:

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

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

Key Responsibilities:

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

Required Qualifications:

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

Preferred Qualifications:

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

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

Mission Summary:

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

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

Key Responsibilities:

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

Required Qualifications:

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

Preferred Qualifications:

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

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

Mission Summary:

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

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

Key Responsibilities:

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

Required Qualifications:

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

Preferred Qualifications:

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

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

As an AWS Cloud Data Engineer, you will be responsible for designing, developing, and maintaining robust data infrastructure solutions to support the organization’s data-driven initiatives. We seek self-driven and motivated individuals who take ownership of their projects. You will collaborate closely with cross-functional teams including project managers, business analysts, and software engineers to ensure the availability, reliability, and scalability of our system.

This role is onsite and can be based at any of the following Shift4 locations: Tampa, FL / Atlanta, GA / Las Vegas, NV / Center Valley, PA

Responsibilities

Technology:

• Work hands on within the cloud data platform to deliver new features, fix issues and ensure best practices.
• Contribute to the technical design and architecture development for parts of the solution. Ensure that best practices are defined and adhered to
• Diagnose and resolve issues with deployed systems (as part of level 3 support).
• Become technically solid for the cloud data platform.
• Evaluate and resolve technical debt, engage in platform modernization and build reliable features.
• Recommend and implement best practices and standards for the cloud data platforms.

People and Leadership

• Work closely with multiple engineering teams, product owners and stakeholders to understand needs and meet data requirements.
• Interface across multiple engineering teams and engineering groups working on various parts of the platform.
• Mentor and develop junior team members.

Process

• Ensure efficient operation of Scrum within the team.
• Analyze and update tools and processes when required.
• Measure key team metrics.

Qualifications

• Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Experience in lieu of a degree may be considered. 
• 3+ years of experience in cloud data engineering. 
• 2+ years working with AWS services including Redshift, AWS Glue, Lambda, DMS, Kinesis, etc.
• 1+ years working with ETL tools (MS SSIS or similar).
• Significant hands-on experience working with databases, schemas, complex queries, data modeling, stored procedures, etc. (MS SQL Server, Postgres and Redshift preferred).
• Excellent communication skills in English, with the ability to collaborate effectively with cross-functional teams and stakeholders.

Additional experience that is a plus to have:

• AWS Certified Data Engineer – Associate
• AWS Certified Cloud Practitioner
• AWS Certified AI Practitioner

The application window will be open until at least April 24, 2026 . This opportunity will remain online based on business needs which may be before or after the specified date.

This role is not eligible for immigration sponsorship.

This role is part of the Growth department on the Digital team. You'll collaborate with ad operations and growth specialists to deliver web, app, and media analytics to key stakeholders. The Growth team works across departments—including sales, marketing, brand, and product—to identify new opportunities and test strategies to drive revenue and improve the customer experience with GFiber’s products.

Role Description

As the Marketing Web Developer you will be the technical lead responsible for managing GFiber’s websites and integration points, supporting digital marketing and sales efforts. You’ll lead, organize, and manage program activities that drive business outcomes while developing systems to proactively identify improvements and drive future optimizations including change management and performance metrics. You'll oversee content management systems, A/B testing tools, and tracking implementations, ensuring smooth operations and optimal performance. Collaboration with cross-functional teams will be key in driving our analytics, marketing, and growth initiatives.

In this role, you'll:

• Engineer and maintain the GFiber web architecture, writing clean, scalable code to integrate marketing technology stacks and third-party services. 
• Implement and manage tools for content management, knowledge management, A/B testing, tracking, and services integration.
• Create technical design documents for new website features and integrations.
• Manage user access, roles, and responsibilities for web tools like Contentful, Optimizely, and KMS Lighthouse.
• Support change requests, issue management, and day-to-day updates related to website content and services, and also align with stakeholders on decisions and changing circumstances.

At a minimum we'd like you to have:

• Bachelor's degree in Digital Marketing, Computer Science, or related fields—or equivalent practical experience.
• 4 years' experience building high-traffic marketing websites and scalable web systems using React, Typescript and JavaScript.
• Experience with A/B testing tools (e.g. Optimizely, Optimize, Test and Target) and experiment configuration.
• Experience implementing and leveraging analytics, tracking and data warehouse platforms (e.g., Google Analytics 4, Google Tag Manager, BigQuery).

It's preferred if you have:

• Experience with headless Content Management Systems (e.g. Contentful, Sanity).
• Experience with ad-tech integrations and custom tracking pipelines for Google Ads and Campaign Manager, ensuring accurate reporting and data attribution for high-traffic marketing sites via API. 
• Experience with AI tools coding tools and LLM technologiesExperience using written and verbal communication to convey technical requirements to both technical and non-technical stakeholders.
• Experience with Python and back-end integrations to support large-scale consumer traffic.

The US base salary range for this full-time position is between $132,800 - $175,100 + bonus + cash award + benefits. As pay varies by location, your recruiter will share more about the specific salary range for your targeted location during the hiring process.

#LI-DNI

Shift4 is expanding globally and seeking a key Senior AWS Cloud Data Engineer to join our team of world-class in-house engineers that will contribute to the technology, architecture and engineering delivery across an AWS Cloud Data Services team.

As a Senior AWS Cloud Data Engineer, you will be responsible for designing, developing, and maintaining robust data infrastructure solutions to support the organization’s data-driven initiatives. We seek self-driven and motivated individuals who take ownership of their projects. You will collaborate closely with cross-functional teams including project managers, business analysts, and software engineers to ensure the availability, reliability, and scalability of our system.

This role is onsite and can be based at any of the following Shift4 locations: Tampa, FL / Atlanta, GA / Las Vegas, NV / Center Valley, PA

Responsibilities

Technology:

• Work hands on within the cloud data platform to deliver new features, fix issues and ensure best practices.
• Contribute to the technical design and architecture development for parts of the solution. Ensure that best practices are defined and adhered to
• Diagnose and resolve issues with deployed systems (as part of level 3 support).
• Become a technical expert for the cloud data platform.
• Evaluate and resolve technical debt, engage in platform modernization and build reliable features.
• Recommend and implement best practices and standards for the cloud data platforms.

People and Leadership

• Work closely with multiple engineering teams, product owners and stakeholders to understand needs and meet data requirements.
• Interface across multiple engineering teams and engineering groups working on various parts of the platform.
• Mentor and develop junior team members.

Process

• Ensure efficient operation of Scrum within the team.
• Analyze and update tools and processes when required.
• Measure key team metrics.

Qualifications

• Bachelors or Masters degree in Computer Science, Information Systems, or a related field. Experience in lieu of a degree may be considered. 
• 5+ years of experience in cloud data engineering. 
• 4+ years working with AWS services including Redshift, AWS Glue, Lambda, DMS, Kinesis, etc.
• 2+ years working with ETL tools (MS SSIS or similar).
• Significant hands-on experience working with databases, schemas, complex queries, data modeling, stored procedures, etc. (MS SQL Server, Postgres and Redshift preferred).
• Excellent communication skills in English, with the ability to collaborate effectively with cross-functional teams and stakeholders.

Additional experience that is a plus to have:

• AWS Certified Data Engineer – Associate
• AWS Certified Cloud Practitioner
• AWS Certified AI Practitioner

#LI-BN1

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.

About Axon 911 

Axon 911 brings together Prepared and Carbyne under Axon. Together, we are creating the only platform that combines modern 911 infrastructure with an AI intelligence layer—helping public safety agencies move faster, make better decisions, and deliver better outcomes in the moments that matter most.

911 is the backbone of public safety, yet the professionals behind it have long been held back by outdated technology. Axon 911 is here to change that. Joining this team means more than taking a job—it means helping shape the future of emergency response and building a safer, more connected world.

Your Impact

As a Senior Sales Engineer, Public Safety (Mountain or Pacific Region), you are both a technical expert and a storyteller. You’ll work closely with Account Executives (AEs), Regional Sales Managers (RSMs), and customers to translate complex technical requirements into compelling solutions. You will lead discovery, configure and demonstrate our platform, manage technical validations, and ensure a smooth handoff to post-sales implementation.

This role is ideal for someone who understands the intersection of technology, public safety operations, and customer success, and who thrives in a mission-driven, fast-paced environment.

What You’ll Do

Pre-Sales Solutioning

• Partner with AEs and RSMs to qualify opportunities, understand customer challenges, and design tailored technical solutions.
• Conduct in-depth discovery with 911 centers, emergency management agencies, and public safety IT teams.
• Deliver engaging product demonstrations, technical workshops, and proof-of-concept sessions tailored to the agency’s environment.
• Lead and respond to RFPs, RFIs, and security questionnaires with accuracy and professionalism.
• Translate complex technical concepts into clear, benefit-focused explanations for non-technical audiences.

Technical Leadership

• Serve as the subject-matter expert for Prepared’s platform architecture, integrations, APIs, and data workflows.
• Provide configuration and system design guidance based on customer requirements, existing CAD/NG911 systems, and IT infrastructure.
• Advise agencies on best practices for network security, system interoperability, and deployment planning.
• Stay up-to-date with public safety software trends, standards (NG911, CAD, RMS, PSAP operations), and competitor offerings.

Sales Enablement & Collaboration

• Work alongside Sales, Product, and Engineering to continuously improve our demo environments, messaging, and field readiness.
• Collect and relay customer feedback to influence product roadmap and technical documentation.
• Support proposal teams with technical content, diagrams, and specifications.
• Assist marketing and partner teams in developing technical collateral, webinars, and events.

Customer Advocacy

• Build trust with agency decision-makers, IT administrators, and operations leaders by demonstrating deep understanding of public safety workflows.
• Ensure technical confidence throughout the sales cycle to accelerate buying decisions.
• Represent Prepared at tradeshows, conferences, and industry events as a technical ambassador.

What You Bring

• 8+ years of progressive experience in public safety, emergency communications, or PSAP operations, with senior-level leadership experience strongly preferred (Director, Assistant Director, Executive Director, or equivalent).
• Demonstrated experience selling, implementing, or enabling public safety software (e.g., NG911 call handling, CAD, RMS, ESInet, radio systems, mass notification, or emergency communications platforms).
• Proven ability to operate as a field-facing technical advisor to Sales—owning discovery, solution design, demonstrations, technical validation, and RFP/RFI responses end-to-end.
• Deep understanding of PSAP workflows, operational constraints, funding models, procurement cycles, and compliance environments, including experience presenting to boards, executives, and elected officials.
• Strong technical fluency across cloud-based platforms, integrations/APIs, network infrastructure, data workflows, and system interoperability within public safety environments.

Additional Requirements

• Track record of building credibility with PSAP directors, IT leadership, emergency management leaders, and dispatch supervisors through consultative, trust-based engagement.
• Experience partnering cross-functionally with Product and Engineering to influence roadmap priorities based on real-world PSAP needs.
• Comfortable operating in high-growth, ambiguous environments with minimal playbooks—able to create structure, demo narratives, and field enablement materials where needed.
• Exceptional executive communication and storytelling skills—able to translate technical capability into operational ROI and mission impact.
• Willingness to travel up to 75% and represent Prepared as a technical ambassador at industry conferences and customer events.

Public Safety Technology & Systems Expertise

Candidates who are well-positioned for success in this role typically bring hands-on experience working with the core technology systems that power emergency communications centers.

This may include experience with:

• 911 call handling systems (CHE) such as VESTA, Viper, or Solacom
 • Computer-Aided Dispatch (CAD) platforms used to manage emergency response workflows
 • Radio console systems supporting multi-agency communications
 • Logging recorders used for call review, compliance, and operational analysis
 • Network and traffic analysis tools, such as Wireshark, used to troubleshoot system performance and integrations

Successful candidates often have direct experience supporting, configuring, troubleshooting, or operating these systems within PSAPs, ECCs, or other mission-critical public safety environments.

Work Location

This is a fully remote role open to candidates based in the United States. Candidates located in the Mountain or Pacific regions are strongly encouraged to apply. Due to the nature of the position, up to 75% travel is required, including customer meetings, training sessions, and industry events.

Benefits that Benefit You

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Medical, dental, and Vision plans
• Fitness Programs
• Emotional & Mental Wellness support
• Learning & Development programs
• And yes, we have snacks in our offices

Benefits listed herein may vary depending on the nature of your employment and the location where you work.

Pay Transparency

Axon offers a comprehensive total compensation package, which includes base salary, a generous annual bonus, and company equity.

The starting base salary for this role ranges from $110,000 to $160,000 annually, excluding commission and bonuses, and varies based on geographic market. Actual base pay will depend on several factors, including level, function, training, transferable skills, work experience, business needs, and location.

Our benefits are designed to support you physically, financially, and emotionally—through life’s major milestones and in your everyday moments. To learn more about our benefits, please visit www.axon.com/careers/benefits.

Mission Summary:

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

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

What You'll Do:

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

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

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

Bonus Points (Nice-to-Haves):

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

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

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

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

Mission Summary:

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

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

Responsibilities:

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

Qualifications:

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

Bonus Skills:

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

Physical Demands:

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

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

Working Environment

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

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

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

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

Mission Summary:

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

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

Responsibilities:

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

Qualifications:

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

Bonus Skills:

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

Physical Demands:

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

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

Working Environment

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

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

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

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

Mission Summary:

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

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

Responsibilities:

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

Qualifications:

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

Bonus Skills:

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

Physical Demands:

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

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

Working Environment

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

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

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

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

Mission Summary:

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

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

Responsibilities:

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

Qualifications:

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

Bonus Skills:

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

Physical Demands:

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

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

Working Environment

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

Motional AD LLC is an Equal Employment Opportunity employer and we welcome all qualified applicants.  All applicants will receive impartial consideration without regard to race, sex, color, national origin, age, disability, veteran status, genetic data, religion, gender identity, sexual orientation or other legally protected status.  Motional AD LLC is a Drug-free workplace.

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

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

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

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

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

What You'll Be Doing:

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

What We're Looking For:

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

Bonus Points (not required):

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

Success Metrics:

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

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

Physical Demands:

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

Travel Requirements (greater than 20%):

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

Working Environment:

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

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

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

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:

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

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

What you'll do:

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

What we're looking for:

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

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

Mission Summary:

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

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

What you'll do:

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

What we're looking for:

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

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

Mission Summary:

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

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

What you'll do:

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

What we're looking for:

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

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

Mission Summary:

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

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

What you'll do:

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

What we're looking for:

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

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

The Staff Systems Safety Engineer:

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

Essential Duties:

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

Qualifications:

Educational Requirements

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

Technical / Specialized Knowledge, Skills, Abilities:

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

Physical Demands:

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

Working Environment:

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

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

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

Mission Summary:

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

What you’ll be doing:

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

What we’re looking for:

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

Bonus Points (not required):

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

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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

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

What You'll Do:

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

What We're Looking For:

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

Bonus Points (Nice-to-Haves):

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

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

Mission Summary:

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

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

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

What You'll Be Doing

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

What We're Looking For

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

Bonus Points (not required): 

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

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 App of the Day.

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

With the growth of our iOS app, being the #18 productivity app in the App Store category and also our recent recognition as Apple's 2025 Design Award for Inclusivity, we find the need for a Senior iOS Engineer to help us support the new user base as well as work on new and exciting projects to push our missing forward.   

This is a key role and ideal for someone who thinks strategically, enjoys fast-paced environments, 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

• Opportunity to lead key engineering and product decisions
• Actively shipping production code for the Speechify iOS app
• Work within a dedicated product team
• Participate in product discussions to shape the product roadmap
• Maintain and enhance the existing complex app architecture

An Ideal Candidate Should Have

• Experience. You've worked on products that scaled to a large user base
• Track record. You have worked on various products from inception to decent traction. You have been responsible for engineering the product
• Customer obsession. We expect every team member whose responsibilities directly impact customers to be constantly obsessed about providing the best possible experience
• Product thinking. You make thoughtful decisions about the evolution of your product and support internal teams and designers into taking the right direction
• Speed. You work quickly to generate ideas 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
• Technical skills. Swift, SwiftUI

Technical Requirements:

• Swift Programming Language
• SwiftUI experience
• Experience in Multithreading Programming
• Working with CI/CD infrastructure
• Experience with Fastlane
• SOLID principles, the ability to write every single class according to SOLID
• Experience with Git and understanding of different Git strategies

What We offer:

• A fast-growing environment where you can help shape the company and product
• An entrepreneurial crew that supports risk, intuition, and hustle
• The opportunity to make a big impact in a transformative industry
• A competitive salary, a collegiate atmosphere, and a commitment to building a great asynchronous culture
• Work on a product that millions of people use and where daily feedback includes users sharing that they cried when they first found the product because it was so impactful on their lives
• Support people with learning differences like Dyslexia, ADD, Low Vision, Concussions, Autism, and Second Language Learners, and give reading superpowers to professionals all over the world
• Work in one of the fastest growing sectors of tech: 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.

Overview

As the Industrial Engineer - Warehouse Design & Automation, you will be a technical leader responsible for designing, engineering, and scaling warehouse facilities across a multi-site fulfillment network. Your primary mission is to translate business demand and growth forecasts into data-driven, buildable warehouse designs that optimize throughput, labor efficiency, space utilization, and cost.

This role partners closely with Operations, Real Estate, Facilities, IT, Finance, and external automation vendors to deliver standardized, scalable solutions for greenfield builds, expansions, and retrofits. You will bring a strong systems mindset, deep understanding of material flow, and a bias for simplicity, operability, and long-term sustainability.

What You’ll Do

Warehouse Design & Engineering

• Design end-to-end warehouse layouts for new facilities, expansions, and retrofits, supporting high-throughput fulfillment operations.
• Engineer material flows from inbound receiving through outbound shipping, ensuring efficient, safe, and ergonomic processes.
• Define building-level requirements including dock counts, clear heights, column spacing, power, floor loading, and equipment zoning, in partnership with cross-functional teams.
• Develop and maintain layout drawings, design assumptions, and engineering narratives for leadership, finance, and vendor review.

MHE & Automation Engineering

• Specify, evaluate, and engineer material handling and automation systems including:
• Conveyors, sorters, and divert systems
• Pick modules, pallet flow, case flow, and mezzanines
• AMRs, AGVs, and goods-to-person solutions
• Packaging, labeling, dimensioning, and weighing systems
  
  
• Develop functional specifications, throughput targets, and redundancy strategies for automation systems.
• Partner with integrators and vendors through RFPs, design reviews, FAT/SAT, commissioning, and go-live support.

Capacity Modeling & Data Analysis

• Build capacity, throughput, and labor models using forecasted volumes, SKU profiles, and order characteristics.
• Analyze peak scenarios, seasonality, and failure modes to stress-test designs.
• Quantify trade-offs between labor, automation, space utilization, service levels, and cost.
• Use post-launch operational data to refine assumptions and continuously improve design standards.

Financial Analysis & Business Case Development

• Develop CapEx and OpEx estimates for MHE and automation investments.
• Support ROI, payback period, and total cost of ownership analyses.
• Partner with Finance and Leadership to support capital planning and investment decisions.
• Drive standardization across facilities to reduce engineering variability and lifecycle cost.

Launch Support & Continuous Improvement

• Support warehouse launches and expansions through go-live and stabilization.
• Partner with Operations, Maintenance, and Controls teams to resolve systemic design issues.
• Perform post-launch audits and feed learnings back into network design standards and playbooks.
• Document and maintain reference designs, engineering standards, and best practices.

What You’ll Need

• Bachelor’s degree in Industrial Engineering, Mechanical Engineering, Systems Engineering, or a related field.
• Alternatively, equivalent hands-on experience designing warehouse automation systems may be considered.
• 5+ years of experience in warehouse design, material handling engineering, or automation.
• Proven experience designing high-volume distribution or fulfillment centers.
• Strong analytical and modeling skills, with advanced proficiency in Excel; SQL, Python, or simulation tools are a plus.
• Proficiency in AutoCAD or similar layout and design tools.
  
  

Preferred Qualifications

• Master’s degree in Industrial Engineering, Mechanical Engineering, Systems Engineering, or a related field.
• Experience in large-scale e-commerce, retail, or 3PL fulfillment networks.
• Familiarity with WMS concepts and system integration dependencies.
• Greenfield warehouse launch experience.
• Experience working directly with automation integrators or MHE vendors.
  
  

Key Attributes

• Strong systems thinker with the ability to design for scale, peak, and failure scenarios.
• Data-driven decision maker who can clearly communicate technical trade-offs to non-technical stakeholders.
• Practical, operations-aware engineer who values simplicity, maintainability, and standardization.
• Builder mindset with a desire to create mechanisms, standards, and repeatable solutions.