Project Engineer: Machine Learning Scientist

Project Engineer: Machine Learning Scientist

The Fraunhofer USA Center for Manufacturing Innovation (CMI) in Boston, MA is part of Fraunhofer USA, a 501 (c) (3) non-profit contract R&D organization. The Industrial Automation team develops turnkey automation solutions for customers from a broad range of industries, including biotech/biomedical, consumer products, aerospace, renewable energy, and fiber optics/photonics. The Energy Systems team works in partnership with clients ranging from the Federal Government and established companies to start-ups to develop, pilot, and validate technologies in building energy systems and grid-integration of renewables. The Biomedical Systems team solves challenging applied research problems for the biomedical community to develop, pilot, and validate technologies in point-of-care diagnostics, rapid microbial testing, automated sample preparation, and tissue engineering. To learn more about our work, please visit: here.

About the Position:

Our scientists and engineers are applying machine-learning algorithms to address challenging problems, such as defect characterization, fault-detection and diagnostics (FDD), and training of high-fidelity data-driven models for control. We work with new and emerging data sources that have appreciable limitations. We seek a motivated team member to apply and develop novel machine-learning approaches with all three teams at CMI. You will identify new opportunities to apply machine learning, work with project teams to scope out, test, and implement approaches to meet technical goals, contribute to new project proposals, and have the opportunity to publish in top-tier journals and conferences. This position has a high degree of growth potential and is an excellent opportunity for a talented and curious scientist to address challenging and impactful problems.

Qualifications

• Strong expertise in Machine Learning and Deep Learning with hands-on implementation experience, particularly with “noisy” real-world problems
• Extensive experience using machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)
• Ability to understand details of an engineering problem, formulate it as an ML problem, and identify promising ML approaches
• Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with research and/or business goals
• Strong research credentials as evidenced by publications in leading ML conferences/journals or demonstrated open-source software development
• PhD and 4+ years of experience in a relevant quantitative discipline (e.g., Computer Science, Electrical Engineering, Mathematics, Operations Research, Optimization, or Data Science). Graduate research experience may count toward work research experience
• Strong verbal and written communication skills and good interpersonal skills
• Ability to work effectively on multiple concurrent projects with limited oversight

Responsibilities

• Drive Center-wide initiatives by identifying promising opportunities to apply and accelerate the application of machine learning models across different areas of the Center’s research
• Develop state-of-the-art machine learning models and apply them to a wide variety of complex tasks aligned with the Center’s core expertise
• Initiate, lead, and execute internal and external R&D projects

In your cover letter, please explain what motivates you to apply and succinctly describe your most relevant work experience.

Applications lacking a cover letter may not be seriously considered.

Fraunhofer USA is an EEO/Affirmative Action Employer and does not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other legally protected status.

Contact

Fraunhofer USA - Center for Manufacturing Innovation
15 Saint Marys Street
Brookline, MA 02446, USA