Singapore, Central, Singapore
Open 6 months, first seen by us 204 days agoProfile training to find bottlenecks in data loading, gradients, and communication
Apply kernel fusion, sharding, and tiling to cut training step time
Optimize distributed training pipelines with PyTorch Distributed
Design and maintain high-performance GPU kernels in Triton or CUDA
Optimize data loading pipelines to maximize training throughput
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
Optimize robust data loading pipelines that maximize training throughput
Strong proficiency in Python
Extensive hands-on experience with PyTorch
Experience optimizing machine learning model execution during training and inference
Bachelor’s, Master’s degree, or PhD in Computer Science, Computer Engineering, or a related technical discipline
Exceptional analytical and problem-solving skills, with a bias for action and a data-driven approach to technical challenges
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.
Open 6 monthsWe first saw this posting 204 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
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Day 204
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 4,442 similar postings that came down, and 9 of Motional’s. Coming down is not always a hire.
12 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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- 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.
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New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.
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.
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.
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.
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:
What we're looking for:
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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Singapore, Central, Singapore
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