Principal Machine Learning Engineer, Data Mining

What you'll do

• Define the data-mining ML roadmap and build end-to-end data pipelines that support active learning, model distillation, and large-scale search.
• Architect and implement systems for fine-tuning, retrieving with, and deploying large models; improve inference efficiency, reliability, and cloud footprint.
• Coordinate with Autonomy and Infrastructure teams, guide phased rollouts, and coach up to 3 engineers.

What they ask for

• BS in Computer Science, Machine Learning, or a related field, or equivalent professional experience.
• 12+ years of hands-on machine learning engineering experience owning enterprise-scale ML systems end to end.
• Deep experience training large-scale models, including distributed multi-node GPU training, data curation, evaluation, and debugging.
• Experience with cloud ML environments (AWS, GCP, or Azure), production deployment, technical roadmaps, and cross-team initiatives.

Nice to have

• MS/PhD in Computer Science, Machine Learning, or a related field.
• Experience in autonomous driving, robotics, multimodal foundation models, model distillation, alignment, retrieval, or agentic workflows.

Pay

$240,000 — $330,000 USD base salary

Tools

AWS, GCP, Azure, TF Serving, Triton, TorchServe

AI focus

Build and optimize multimodal foundation-model post-training systems, including model alignment and distillation, parameter-efficient fine-tuning, RL-driven reasoning, agentic workflows, and efficient deployment for autonomous-vehicle data mining.