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Machine Learning Systems Engineer

Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.

Open 5 months, first seen by us 178 days ago
Pay
USD 144,000–192,000/yearAnnual period assumed — pay source
Salary Range $144,000—$192,000 USD Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.
Read the full posting
Work setting
Remote — work setting source
Listed location: Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.
Read the full posting
Employment
Not stated

What you’ll work on

Full posting
  • Profile training runs to find bottlenecks in data loading, gradients, and communication

  • Apply kernel fusion, sharding, and tiling to cut training step time

  • Optimize distributed training pipelines in PyTorch Distributed

  • Design and maintain high-performance GPU kernels in Triton or CUDA

  • Build data loading pipelines that maximize training throughput

From the employer’s posting
Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication
Implement optimizations like kernel fusion, sharding, and tiling to improve step time
Optimize distributed training pipelines using frameworks such as PyTorch Distributed
Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads
Optimize robust data loading pipelines that maximize training throughput
Education & alternatives
What we're looking for: - Education: Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline. - Software Engineering: Strong proficiency in Python.
Apply at Motional

Posting record

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Open 5 monthsWe first saw this posting 178 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
May 11, 2026178 days ago
Recorded sightings
100
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$144K–$192K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 178

Up longer than most. Similar jobs usually come down between day 6 and day 70.

Well past Motional’s usual: its jobs come down by about day 61.

From 4,452 similar postings that came down, and 9 of Motional’s. Coming down is not always a hire.

Motional is hiring

13 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Hiring has slowed
  • Its jobs tend to stay up a long time
  • 8% of open jobs were reposted
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • PyTorch
Where the posting names them
- Education: Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline. - Software Engineering: Strong proficiency in Python. - ML Frameworks: Extensive hands-on experience with PyTorch.
What you'll be doing: - Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time. - Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
- Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time. - Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed. - Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
- Software Engineering: Strong proficiency in Python. - ML Frameworks: Extensive hands-on experience with PyTorch. - ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.

Your next step

Complete your application on motional.com. The employer’s form will show what is required.

Applying through Greenhouse

  • No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
  • Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.

Already applied? Track this application

Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

Mission Summary:

We are looking for a Machine Learning Systems Engineer to join our ML Acceleration team. In this role, you will be responsible for the core systems that enable our researchers to train frontier models at scale, focusing obsessively on speed, cost, reliability, and throughput. You will work at the intersection of machine learning research and high-performance systems engineering. Your work will directly impact our ability to scale large-scale distributed model training and reduce the time-to-convergence for our next generation of models.

What you'll be doing:

  • Performance Profiling & Optimization: Utilize profiling tools (e.g., Nsight, PyTorch Profiler) to identify bottlenecks in data loading, gradient computation, and communication. Implement optimizations like kernel fusion, sharding, and tiling to improve step time.
  • Distributed Training: Optimize distributed training pipelines using frameworks such as PyTorch Distributed.
  • Kernel Development: Design and maintain high-performance GPU kernels in Triton or CUDA for state-of-the-art ML workloads.
  • Data Pipeline Engineering: Optimize robust data loading pipelines that maximize training throughput.

What we're looking for:

  • Education: Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline.
  • Software Engineering: Strong proficiency in Python.
  • ML Frameworks: Extensive hands-on experience with PyTorch.
  • ML Knowledge: Experience optimizing machine learning model execution during training and inference, alongside a strong understanding of fundamental machine learning concepts, architectures, and processes.
  • Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges.

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

The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process. 

Candidates for certain positions are eligible to participate in Motional’s benefits program. Motional’s benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.

Salary Range
$144,000—$192,000 USD

Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.

Our journey is always people first.

We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.

Higher purpose, greater impact.

We’re creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it’s not only good for our business, it’s the right thing to do.  

Scale up, not starting up.

Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We’re driven to scale; we’re moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.

Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit  www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.

Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.

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Pay
Salary Range $144,000—$192,000 USD Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We’re driven by something more.
Location & working pattern

Boston, Massachusetts, United States; Las Vegas, Nevada, United States; Pittsburgh, Pennsylvania, United States; Remote U.S.

- Problem Solving: Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges. We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote. The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
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