Staff Machine Learning Engineer
$200,000–$220,000 year
Hybrid · Boston, Massachusetts, United States or North Bethesda, Maryland, United States
Job Summary
Staff Machine Learning Engineer role leading end-to-end ML system design and the real-time ML serving architecture for the DFM AI + IQE integration. Responsibilities include requirements gathering through release, building high-performance AI/ML layers, defining data contracts for model inputs/outputs, implementing MLOps, governance, and observability for mission-critical, public-marketplace partner integrations; building cloud-based production systems powering real-time endpoints and MLOps; solving cross-domain challenges; setting multi-quarter roadmaps; ensuring quality and security; collaborating with engineers, product managers, data scientists, and business stakeholders; mentoring other engineers; staying current with advances in ML/AI and bringing new tools into practice.
Required Qualifications
- Bachelor's degree in a STEM field
- 6-8 years of experience in machine learning engineering
- Proficiency in Python and ML frameworks such as TensorFlow or PyTorch
- Hands-on experience deploying real-time ML products at scale in cloud environments (AWS strongly preferred)
- Experience with MLOps practices: model monitoring, data and concept drift detection, automated retraining and redeployment
- Proficiency with CI/CD pipelines (e.g., Github Actions) and infrastructure as code (e.g., Terraform)
- Experience with containers and Kubernetes
- Ability to operate independently on ambiguous assignments and communicate across engineering, product, and business stakeholders
- Knowledge of state-of-the-art modeling techniques including transformers and large language models
- Background in manufacturing, supply chain, or marketplace environments is a plus
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