Lead ML Data Mining Architect for Multimodal AI

Motional AD Inc.; Boston, Northern (MA, KY); Hybrid; USD 240,000 - 330,000; Full time

Job summary

Motional AD Inc. is seeking a Principal Machine Learning Engineer for Data Mining in a remote U.S. setting. The role focuses on leading ML system design and data pipelines for multimodal data, with an emphasis on edge-case discovery and scalable model deployment.

You will drive cross-functional initiatives, mentor engineers, and shape long-term foundational investments while delivering impactful, scalable solutions for autonomous driving software.

Qualifications

• BS in Computer Science, ML, or related field, or equivalent experience.
• 12+ years of hands-on ML engineering with end-to-end ownership.
• Proven track record delivering enterprise-scale ML systems.
• Experience training large-scale models, distributed across multi-node clusters.
• Ownership of a technical roadmap with balancing impact, quality, and compute costs.

Responsibilities

• Define multi-year ML roadmap for Omnitag data-mining platform.
• Own full ML data pipelines lifecycle and distill teacher models into student models.
• Design architecture for billion-parameter models and optimize inference latency.
• Coordinate cross-functional rollout and align ML with Autonomy and Infrastructure teams.
• Lead and grow a pod, mentoring up to 3 engineers and improving tooling.

Skills

Machine Learning

Distributed training

Edge-case analysis

Leadership

Cross-team collaboration

MLOps

Model distillation

Inference optimization

Cloud deployment

Education

BS in Computer Science or related field

MS/PhD (bonus)

Tools

TF Serving

Triton

Distributed training frameworks

Cloud platforms (AWS/GCP/Azure)

Job description

Motional AD Inc. is seeking a Principal Machine Learning Engineer for Data Mining in a remote U.S. setting. The role focuses on leading ML system design and data pipelines for multimodal data, with an emphasis on edge-case discovery and scalable model deployment.

You will drive cross-functional initiatives, mentor engineers, and shape long-term foundational investments while delivering impactful, scalable solutions for autonomous driving software.