Level

CoVar

Machine Learning Engineer

AI in this role

pytorchtensorflow
computer-visionnlp

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
  • Excellent technical communication skills
  • Ability to work in Durham, NC (relocation assistance available)
  • Eligibility for US security clearance (US citizenship is required)

Bonus skills

  • Department of Defense project experience
  • Active US security clearance (secret or higher)

Benefits

  • Competitive salary, cash bonus, equity structure, and 401k with employer contributions
  • Excellent health care coverage, including dental and vision plans
  • Parental leave
  • Short-term and long-term disability insurance
  • Life insurance
  • Flexible work schedule
  • Tuition support
  • PTO and paid holidays

Visit us: www.covar.com

How we score this

Machine Learning Engineer at CoVar scores 94 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Classification

AI Level 4. Building AI systems is the job itself: without AI, the role would not exist.

  1. AI Level 480 to 100
  2. AI Level 360 to 79
  3. AI Level 240 to 59
  4. AI Level 10 to 39

Bands come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionNlpPyTorchTensorFlow

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. What are the limits of PyTorch that you've run into, and how did you work around them?
  4. What's a project where you used TensorFlow hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Computer Vision, Nlp, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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