Machine Learning Data Engineer

Oak Ridge National Laboratory - Oak Ridge, TN

Full-time - Mid Level

Oak Ridge, TN

5,001-10,000 employees

Professional, Scientific, and Technical Services

About the position

The Advanced Computing in Health Sciences (ACH) section at the Oak Ridge National Laboratory (ORNL) is seeking qualified applicants for a Machine Learning Engineer position focused on health research projects. This role involves working with HIPAA compliant research data, providing an opportunity to engage in some of the most challenging and impactful research and development programs in healthcare informatics, bioinformatics, high-performance computing, and deep learning. The successful candidate will be part of a collaborative research and development environment, tasked with designing and implementing robust, high-performance applications for biomedical research. We are looking for an innovative thinker who can design and implement machine learning, statistical, probabilistic, or algorithmic solutions to real-world problems in healthcare and biomedical research. As a U.S. Department of Energy (DOE) Office of Science national laboratory, ORNL has an extraordinary 80-year history of addressing the nation's biggest challenges. With a dedicated and creative staff of over 6,000 people, ORNL is committed to fostering diversity, equity, inclusion, and accessibility (DEIA) within its workforce. This commitment is essential for executing ORNL's broader mission to accelerate scientific discoveries and translate them into solutions for energy, environment, and security issues facing the nation.

Responsibilities

• Independently solve a variety of sophisticated technical problems for scientific and technical projects.
• Develop high-quality code following best practices in the community for documentation, provenance, version control, etc.
• Manage, maintain, and refactor ML codebases, pipelines, and workflows.
• Collaborate closely with research staff to design and implement novel ML approaches.
• Implement scalable ML methods and workflows for high-performance computing (HPC) resources, in close collaboration with research staff and computing technical staff.
• Mobilize and lead data analysis activities on projects with a focus on common deliverables, goals, and timelines.
• Troubleshoot data analysis issues, including implementation issues, hyper-parameter choices, and modeling decisions.
• Assist in preparation of manuscripts and dissemination of research results in publications and conferences.
• Work on a variety of data analysis assignments in collaboration with scientists and engineers.
• Work in secure enclaves and open computing environments on a wide variety of applied areas.
• Conduct tasks independently and communicate optimally to team members and stakeholders.
• Deliver ORNL's mission by aligning behaviors, priorities, and interactions with our core values of Impact, Integrity, Teamwork, Safety, and Service.
• Promote diversity, equity, inclusion, and accessibility by encouraging a respectful workplace.

Requirements

• B.S. and 5+ years of relevant experience, or an M.S. and 4+ years of relevant experience.
• Degree area should be in Computer Science, Statistics, Information Systems, Engineering, or closely related field.
• Significant expertise with the Python ecosystem for data science.
• Significant expertise with PyTorch or Tensorflow.

Nice-to-haves

• Foundational understanding of supervised and unsupervised learning, reinforcement learning, and deep learning.
• Experience with large, multimodal datasets.
• Experience developing scalable ML algorithms and workflows for HPC resources.
• Experience working on Linux/Unix platforms.
• Self-disciplined work ethic and eagerness to tackle ambitious research problems.
• Experience with healthcare informatics and clinical data is highly desired.
• Excellent written and oral communication skills.
• Ability to function well in a fast-paced research environment, set priorities to accomplish multiple tasks within deadlines, and adapt to constantly evolving needs.

Benefits

• Medical and retirement plans
• Flexible work hours
• On-site fitness, banking, and cafeteria facilities
• Prescription Drug Plan
• Dental Plan
• Vision Plan
• 401(k) Retirement Plan
• Contributory Pension Plan
• Life Insurance
• Disability Benefits
• Generous Vacation and Holidays
• Parental Leave
• Legal Insurance with Identity Theft Protection
• Employee Assistance Plan
• Flexible Spending Accounts
• Health Savings Accounts
• Wellness Programs
• Educational Assistance
• Relocation Assistance
• Employee Discounts