Senior ML Engineer – Embodied AI Scaling Foundations

General Motors

. Design and run experiments connecting data composition to model behavior, including dataset mixtures, sampling strategies, curricula, and scaling-law studies .

Posted 9/29/2026full-timeUnited StatesSenior💰 $159,300 - $230,700 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in machine learning fundamentals, including experimental design and data-centric methodologies, with proficiency in Python and PyTorch for training large-scale models. Strong ability to communicate complex results effectively to both technical and non-technical stakeholders.

Highest-signal resume keywords

Machine Learning FundamentalsPython ProficiencyPyTorch ExperienceData-Centric MLLarge-Scale Model Training

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Experimental DesignBaseline SelectionAblation AnalysisSignal-Versus-Noise EvaluationData CurationData LabelingData AnalysisSQLSparkReinforcement Learning

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

NumPyPandasMulti-GPU TrainingMulti-Node Datasets

Certifications & Qualifications

Master's or PhD in Computer ScienceRoboticsMachine Learning

Industry Keywords

Foundation ModelsImitation LearningTrajectory GenerationAutonomous DrivingSim-to-Real Transfer

Tech Stack

Tools & technologies

Node.jsNumpyPandasPythonPyTorchSparkSQL

About the role

Key responsibilities & impact

Design and run experiments connecting data composition to model behavior, including dataset mixtures, sampling strategies, curricula, and scaling-law studies
Apply self-supervised pre-training, imitation learning, reinforcement learning, and foundation-model fine-tuning to driving behavior, trajectory generation, and perception tasks
Develop data curation and mining methods, including auto-labeling, deduplication, difficulty and uncertainty estimation, and long-tail and out-of-distribution scenario discovery
Define offline metrics and evaluations that predict on-road behavior
Trace model failures to root causes in data and specify data needed to address them
Train models at scale across large multi-GPU and multi-node datasets
Partner with platform teams on required pipelines and tooling
Collaborate with cross-functional teams to bring models into onboard driving systems
Document learnings and best practices
Follow relevant literature and incorporate promising advances into recipes and evaluations

Requirements

What you’ll need

Master's or PhD in Computer Science, Robotics, or Machine Learning
Strong machine learning fundamentals, including experimental design, baseline selection, ablation analysis, and signal-versus-noise evaluation
Proficiency in Python and PyTorch
Experience training models on large datasets
Hands-on experience with data-centric ML, including curation, sampling, labeling, or evaluation of large training sets
Working knowledge of large-scale foundation models and pre-training, fine-tuning, and alignment
Solid data analysis skills using NumPy and Pandas; SQL or Spark for large datasets
Demonstrated ability to deliver applied ML results under real-world constraints and timelines
Clear communication of results and limitations to engineers and non-experts
Preferred: PhD, publications, or open-source contributions in representation learning, multimodal or vision-language models, generative models, reinforcement learning, or data-centric ML
Preferred: Experience with robotics, autonomous driving, or other embodied AI systems
Preferred: Experience with synthetic and simulation data, including sim-to-real transfer
Preferred: Familiarity with production ML deployment workflows

Benefits

Comp & perks

Medical, dental, and vision benefits
Health Savings Account
Flexible Spending Accounts
Retirement savings plan
Sickness and accident benefits
Life insurance
Paid vacation and holidays
Tuition assistance programs
Employee assistance program
GM vehicle discounts
Relocation benefits may be available
Incentive pay program with payouts based on company, job-level, and individual performance