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Protolabs

ML Engineer AI COE

San Francisco, CAOn-siteFull-time$140k – $220k / year

About this role

Protolabs - IC4 - ML Engineer AI COE IC4 - ML Engineer AI COE Hyderabad Technology – Software Engineering / Full-time / On-site apply for this job Join the team as our new ML Engineer, AI Center of Excellence (IC4) India | AI Center of Excellence Protolabs is a digital manufacturing company that turns CAD files and technical drawings into physical parts - fast and at scale. Our AI Center of Excellence builds machine learning systems that empower core manufacturing workflows such as manufacturability analysis, predictive maintenance, and automated part routing to the right expert. We are looking for a Machine Learning Engineer to join the AI COE and support ML and DL systems end-to-end - from problem framing and experimentation through to production deployment. You will work on complex, domain-specific ML problems in manufacturing, applying and adapting state-of-the-art approaches to new challenges and shipping solutions that run in live production environments. What You'll Do: Build & Own ML/DL Systems - Apply ML/AI solutions with awareness of business needs, system constraints, and business context. - Build and own ML/DL models across complex data types - geometries, part metadata, transactional data, and free-text notes. - Own small-to-medium ML/DL subsystems and features end-to-end. - Contribute NLP and document understanding pipelines for technical drawings and unstructured manufacturing specs; build reusable components on our AWS Bedrock-based AI Platform. Experimentation & Technical Problem Solving - Tackle different complex ML problems: identify data issues, navigate model choices, and design clear experiments. - Work independently on assigned ML tasks while collaborating across teams. - Suggest improvements at the feature level; explore and evaluate new techniques with guidance. Collaboration & Mentorship - Mentor junior peers to grow into ML; provide solid code, testing, and reviews. - Contribute to feature-level design discussions a

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