More jobs:
AI/ML Platform Engineering Lead; Python - Onsite
Job in
Ann Arbor, Washtenaw County, Michigan, 48113, USA
Listed on 2026-03-01
Listing for:
Conexess Group
Full Time
position Listed on 2026-03-01
Job specializations:
-
Engineering
AI Engineer
Job Description & How to Apply Below
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.
WhyThis 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.
- 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.
- 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.
- 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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