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AI/ML Platform Engineering Lead (Python) - Onsite
AI/ML Platform Engineering Lead (Python) - OnsiteConexess Group, LLC  • Ann Arbor, MI
AI / ML Platform Engineering Lead (Python) - Onsite

AI / ML Platform Engineering Lead (Python) - Onsite

Conexess Group, LLC • Ann Arbor, MI
[job_card.variable_days_ago]
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  • [job_card.full_time]
[job_card.job_description]

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, TensorFlow, 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 years of related experience with a Bachelors degree, or years of experience and a Masters Degree

    • LI-RS

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