Principal Machine Learning Engineer, Data Mining

• BS in Computer Science, Machine Learning, or a related field, or equivalent professional experience.
• 12+ years of hands-on machine learning engineering experience, with a proven track record of owning the end-to-end development cycle of enterprise-scale ML systems, from experiment design through infrastructure, testing, rollout, monitoring, and iteration.
• Exceptional technical maturity, with a track record of building and shipping impact that is innovative, broad in reach (affecting many teams or orgs), and pays future dividends for the company.
• Proven ability to solve technical problems that few others can, the person others seek out for complex ML infrastructure, deep learning architectures, and production optimization.
• Deep experience training large-scale models from the ground up, including distributed training across multi-node GPU clusters, data pipeline and curation strategy, scaling and evaluation methodology, and the practical debugging of large training runs.
• Demonstrated ownership of a technical roadmap for a team or problem area, including balancing competing objectives (impact, quality, engineering time, compute cost) and making deliberate tradeoffs between long-term foundational investment and short-term tactical goals.
• Ability to create clarity from ambiguous, complex problems, decomposing them concisely, defining objectives, and establishing measures of progress for yourself and your team.
• Deep, generalist ML expertise spanning massive-scale model training, hardware-optimized deployment, and production ML orchestration in cloud environments (AWS, GCP, or Azure).
• Experience leading cross-team initiatives, including coordinating phased rollouts and migrations across dependent teams, and mentoring engineers to raise the bar around you.
• Strong oral and written communication skills. You can clearly explain complex technical problems using data and analysis, and communicate proposals in a way that earns buy-in and creates alignment.

• MS/PhD in Computer Science, Machine Learning, or a related field.
• Experience as a Tech Lead Manager (TLM) or in direct people management, coaching and growing small teams of 2–3 engineers.
• Background in autonomous driving, robotics, or complex real-time decision-making systems.
• Experience with massive-scale ML data mining, multimodal foundation models, and embodied AI.
• Hands-on experience pretraining or post-training a foundation model, data curation at scale, pretraining or continued-pretraining recipes, SFT/RLHF or other alignment methods, and evaluation harness design.
• Experience with model compression and adaptation at scale, knowledge distillation (teacher/student), parameter-efficient fine-tuning, or quantization for high-throughput inference.
• Experience with large-scale retrieval or search systems, or RL for reasoning and decision-making.
• Deep knowledge of enterprise model serving (TF Serving, Triton, TorchServe) and modern MLOps platforms.
• Experience building agentic pipelines or LLM-driven reasoning and tool-use workflows.
• A strong portfolio of publications, patents, or significant open-source contributions that demonstrates influence on the broader engineering community.

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.

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.