Senior AI/ML Engineer – Data Scaling, Embodied AI Data Foundations

General Motors

Senior AI/ML Engineer developing data-centric models and scaling datasets for General Motors’ autonomous driving systems. Improving safe driving behavior through real and synthetic data.

Posted 9/10/2026full-timeMarkham • 🇨🇦 CanadaSenior💰 CA$125,000 - CA$174,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Expertise in data-centric machine learning and model training, with a strong foundation in experiment design and data analysis. Proficient in Python and PyTorch, capable of developing and deploying advanced AI solutions for autonomous driving applications.

Highest-signal resume keywords

Python ProficiencyPyTorch ExperienceData-Centric Machine LearningExperiment DesignLarge-Scale Model Training

ATS Keywords

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Hard Skills

Machine Learning FundamentalsExperiment DesignData CurationModel Fine-TuningData Analysis with NumPyData Analysis with PandasSQLSparkReinforcement LearningImitation Learning

Soft Skills

Clear CommunicationCollaboration

Tools & Technologies

Multi-GPU TrainingMulti-Node DatasetsAuto-Labeling ToolsData Pipelines

Certifications & Qualifications

Master's or PhD in Computer ScienceMaster's or PhD in RoboticsMaster's or PhD in Machine Learning

Industry Keywords

Autonomous DrivingFoundation ModelsSynthetic DataSimulation DataEmbodied AI Systems

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 and use evidence to guide model and data decisions.
Trace model failures to root causes in data and specify the 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.
Develop data-centric AI solutions to improve autonomous driving performance using real and synthetic data.

Requirements

What you’ll need

Master's or PhD in Computer Science, Robotics, Machine Learning.
Strong ML fundamentals, including experiment design, baseline selection, ablation analysis, and signal-versus-noise evaluation.
Proficiency in Python and PyTorch, with 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.
GM does not provide immigration-related sponsorship for this role; applicants must not require GM immigration sponsorship now or in the future.
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

Paid time off including vacation days, holidays, and supplemental benefits for pregnancy, parental and adoption leave.
Healthcare, dental and vision benefits including health care spending account and wellness incentive.
Life insurance plans to cover you and your family.
Company and matching contributions to a Defined Contribution Pension plan to help you save for retirement.
GM Vehicle Purchase Plan for you, your family, and friends.
Role-related assessment(s) and/or pre-employment screening where applicable.
Reasonable accommodations for job seekers with disabilities.