Research Principal Engineer, Machine Learning
Milford, MA, United States
USD 106K-155K (estimate) Senior-level Full Time
Tasks
- Apply Bayesian optimization for experimental design
- Apply generative modeling for research workflows
- Build end to end ML pipelines for data preparation modeling validation and deployment
- Collaborate with cross-functional teams to drive adoption
- Communicate AI and ML concepts to non ML audiences
- Develop training materials and learning programs for AI ML capabilities
- Establish best practices standards and metrics for AI ML adoption
- Identify high value AI ML use cases for research workflows
- Mentor scientists engineers and interns
- Serve as technical lead for applied AI ML research projects
- Source and configure AI ML capabilities into engineering processes
- Use AI ML to extract knowledge from internal data and documentation
- Use surrogate modeling for accelerated research
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | Bayesian optimization | Data Preparation | Data-driven | Data-driven experimental design | Experimental Design | Generative Modeling | Machine Learning | Model Deployment | Model Validation | PyTorch | Python | Scikit-learn | Surrogate modeling | TensorFlow
Education
Regions
Countries
States
Cities
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