Pay: $401,000 — $401,000 USD per year

Employer job description

From CoVar's posting. “We” and “our” refer to the employer.

Machine Learning Engineer

About CoVar

CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the DoD detect enemies and threats, help biomedical researchers find new cures for diseases, and help monitor machinery to prevent injuries and environmental catastrophes. We are passionate engineers, dedicated to pushing the bounds of what AI/ML can do in the real world.

About this position

You will help CoVar develop software and machine learning algorithms to solve real-world customer problems. You will work with data, develop algorithms, evaluate results, and write the production code that goes onto real-world systems. You will have the opportunity to present your work to high-level customers in the DoD and in the industry. The position includes opportunities to publish novel work in both classified and unclassified settings.

Qualifications

Applicants should have expertise in Python (including NumPy, pandas, and other packages) and either PyTorch or TensorFlow. Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves, confusion matrices) are necessary. Knowledge of classical machine learning (e.g., support-vector-machines, logistic regression) are valued. Applicants are ideally familiar with computer vision algorithms like object detection networks (e.g., YOLO, CenterNet) and modern image classification techniques. Previous experience with DoD customers is a plus.

Minimum qualifications

Software expertise: Python and associated numerical and analytics packages (NUMPY, PANDAS, etc.); git; PYTORCH or TensorFlow; CI/CD pipelines and regression testing.
AI/ML expertise: Machine learning fundamentals; Deep knowledge of state-of-the-art in any of the following: computer vision (preferred), natural language processing, classical machine learning, Bayesian models, etc.
B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field