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AI​/ML Platform Engineering Lead; Python - Onsite

Job in Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listing for: Conexess Group
Full Time position
Listed on 2026-03-01
Job specializations:
  • Engineering
    AI Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: AI/ML Platform Engineering Lead (Python) - Onsite

Job Description / Preferred Qualifications

Join our AI/ML engineering team to build the backbone that powers production AI. As an AI/ML Platform Engineering Lead, you’ll architect and scale our MLOps infrastructure, enabling secure, reliable, and fast deployment of machine learning models across cloud and air gapped environments. This is a hands-on leadership role where you’ll mentor engineers, collaborate with hardware teams, and deliver AI solutions that transform semiconductor manufacturing.

Why

This Role Is Compelling
  • Growth:
    You are empowered to make decisions to release product. Clear path for leadership and technical advancement in a fast-evolving AI domain with a strong and young team to help shape their careers.
  • Impact:
    Ship AI solutions that directly reach customers and shape next-gen manufacturing.
What You’ll Do
  • Design, deploy and scale AI/ML platforms for model training and inference.
  • Implement CI/CD pipelines for models and data workflows, ensuring reproducibility and compliance.
  • Develop tools and frameworks that empower ML engineers to move from prototype to production seamlessly.
  • Collaborate with cross-functional teams—including hardware and software—to integrate AI into instruments and factory workflows.
  • Establish observability and governance for model performance, drift detection, and reliability.
  • Mentor engineers and champion best practices in platform engineering and MLOps.
What We’re Looking For
  • Strong programming skills in Python; experience with ML frameworks (PyTorch, Tensor Flow, Keras).
  • Expertise in MLOps tools (MLflow, Kubeflow), container orchestration (Kubernetes, Docker), and infrastructure automation (Terraform).
  • Experience deploying models in secure or disconnected environments (air gapped, on-prem).
  • Familiarity with cloud platforms (AWS, Azure, GCP) and hybrid architectures.
  • Proven ability to lead technical design discussions and mentor engineering teams.
Minimum Qualifications
  • Requires a minimum of 5 years of related experience with a Bachelors degree, or 3 years of experience and a Masters Degree
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