Senior/Principal Machine Learning Engineer

University of Michigan Health-West; Northern (KY); Hybrid; USD 200,000 - 300,000; Full time

Job summary

University of Michigan Health-West is seeking a Senior or Principal Machine Learning Engineer to build production-grade ML systems for autonomous driving. You will develop perception, prediction, and planning components for next-generation navigation platforms in a remote U.S.

setting. Candidates should have an advanced degree in a technical field, 5+ years of ML/vision experience, and hands-on experience with PyTorch or TensorFlow, large-scale data processing, and deploying models from research

Qualifications

• Advanced expertise in ML and/or computer vision with practical deployment experience.
• 5+ years of professional ML/DS experience.
• Experience taking models from research to production.
• Strong collaboration across product, data, and engineering teams.

Responsibilities

• Develop ML solutions from experimentation to production.
• Explore and implement new ideas using deep learning and foundation models.
• Design models for object detection, tracking, prediction, motion planning, and mapping.
• Manage full lifecycle of ML projects: data exploration, training, validation, verification.
• Collaborate with product teams, simulation engineers, and algorithm specialists.
• Evaluate and improve model performance for real-world deployment.

Skills

Machine learning

Computer vision

Deep learning

Large-scale data processing

Independent work

Cross-functional collaboration

Education

Master's/PhD in CS/CE/Math/Physics

Tools

PyTorch

TensorFlow

Job description

Senior/Principal Machine Learning Engineer

Remote (United States)

Status: Full-Time

Compensation: $200,000 - $300,000 annually

About the Role

This opportunity is for a Senior or Principal Machine Learning Engineer focused on building advanced machine learning systems for autonomous driving technologies. The role involves developing production-ready ML solutions that support perception, prediction, and planning systems used in next-generation autonomous navigation platforms.

The position requires deep expertise in machine learning, computer vision, and large-scale data processing, along with experience taking machine learning models from research and experimentation through deployment and commercialization.

What You’ll Do

• Develop machine learning solutions that support autonomous driving systems from experimentation through full-scale production.
• Explore and implement new ideas using deep learning, neural networks, and large foundation models.
• Design and build models for object detection, tracking, prediction, motion planning, control systems, and online mapping.
• Manage the full lifecycle of machine learning projects including data exploration, training, validation, and model verification.
• Collaborate with product teams, simulation engineers, and algorithm specialists to integrate machine learning technologies into autonomous driving systems.
• Evaluate and improve model performance to support real-world deployment scenarios.

Qualifications

• Master’s or Ph.D. in Computer Science, Computer Engineering, Mathematics, Physics, or a related technical field.
• Strong expertise in machine learning and/or computer vision using advanced and emerging techniques.
• Experience working with deep learning frameworks such as PyTorch, TensorFlow, or similar platforms.
• Knowledge of generative models, model distillation, or model inference acceleration techniques.
• Strong understanding of machine learning system design and large-scale data processing.
• Ability to work independently while collaborating on complex, cross-functional engineering projects.
• Experience with research publications in top conferences or journals is considered a strong advantage.
• 5+ years of relevant professional experience in machine learning or related fields.
• Opportunity to work on cutting-edge autonomous navigation technology.
• Ability to contribute to breakthrough innovations in next-generation transportation systems.
• Fast-paced and collaborative engineering environment.
• Exposure to cross-team research and product development initiatives.
• Opportunity to help shape the future of autonomous mobility.
• Competitive compensation and benefits package.

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