Machine Learning Engineer (Materials)

CFD Research Corporation • Dayton, OH

11d • Onsite

About The Position

The engineer in this role will join a multidisciplinary R&D team focused on the development of machine learning algorithms focused on applications including, but not limited to, materials science, analytical chemistry, and microelectronics. We are looking for an engineer with core competencies in the areas of data-driven and quantitative modeling, as well as having the necessary science and engineering background to develop and deliver effective machine learning-based software solutions for our customers. This is a materials/chemistry focused role. The ideal candidate would have a background in both machine learning, and materials science and/or chemistry, physics, etc. The successful candidate will actively participate in all stages of the model life cycle, from ideation to deployment, for tasks that include, but are not limited to, exploratory data analysis, dataset preparation, model implementation, model training, model evaluation, model-based optimization, synthetic data generation, and first-principles modeling and simulation. They will collaborate with other engineers, subject matter experts, and program managers to achieve deployment of the algorithms to edge devices, desktop applications, and cloud services.

Requirements

• A background in materials science, chemistry, physics, etc.
• Strong programming skills in Python
• Experience with machine learning frameworks such as PyTorch or TensorFlow/Keras
• Familiarity with machine learning methods for classification, regression, clustering, dimensionality reduction, generative modeling, etc.
• Candidate must be a US Citizen and meet eligibility to work for any employer.
• Be available to work in Huntsville, AL or Dayton, OH

Nice To Haves

• Experience in applying machine learning to computer vision, forecasting, and natural language processing is a plus
• Experience with CUDA and/or OpenCL is a plus
• Experience deploying machine learning models to production environments
• Experience in a research and development environment
• A history of peer-reviewed publications

Responsibilities

• Actively participate in all stages of the model life cycle, from ideation to deployment.
• Perform exploratory data analysis.
• Prepare datasets.
• Implement machine learning models.
• Train machine learning models.
• Evaluate machine learning models.
• Perform model-based optimization.
• Generate synthetic data.
• Conduct first-principles modeling and simulation.
• Collaborate with other engineers, subject matter experts, and program managers to achieve deployment of algorithms to edge devices, desktop applications, and cloud services.

Benefits

• Competitive salaries
• Employer matching 401(k)
• Employee Stock Ownership Plan (ESOP)
• Highly competitive insurance package, including medical, vision, and dental insurance
• Company paid leave
• Compensation time
• Parental leave
• Long-term and short-term disability
• Accidental death and dismemberment
• Life insurance

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level