Software Engineer

AI in this role

pytorchscikit-learn

prompt-engineering

Software Engineer

About CoVar

CoVar is a small, mission-driven AI/ML R&D software company based in Durham, NC and McLean, VA. We build advanced software and machine learning systems that help the Department of Defense detect threats in high-stakes environments and enable biomedical researchers to accelerate discoveries that save lives. Our team is composed of curious, passionate engineers who care deeply about using AI to solve real-world problems that matter.

About this position

We are looking for a motivated, detail-oriented Software Engineer who thrives in an environment where reading, understanding, and improving complex codebases is just as important as writing new code. In this role, you will develop and maintain real-time, computationally intensive applications involving data processing, real-time communications, and machine-learning algorithm integration.

You’ll work closely with a team of ML engineers and software developers, contribute to system architecture and performance optimization, and help ensure our tools are robust, efficient, and production ready. You will have the opportunity to work on meaningful, high-impact projects in a close-knit engineering team. If you enjoy building systems end-to-end, optimizing performance, and understanding how software interacts with hardware at a deep level, you’ll fit right in.

Important Note:

This is a software engineering role and not a prompt engineering role. Candidates with strong LLM prompting skills but limited understanding of software engineering fundamentals will not be successful here.

Minimum qualifications

B.S. in Computer Science or related field, preferably M.S., Ph.D, and/or 3+ years of experience
Expertise in Python with a minimum of two years of demonstrated hands-on professional development experience and exposure to scientific/computational libraries such as NumPy, SciPy, pandas, scikit-learn, PyTorch, etc.
Experience developing real-time, computationally-focused applications
Working knowledge of SQL and experience with one or more of MySQL, PostgreSQL, or SQLite
Strong fundamental understanding of computing hardware architectures and how they influence software architectural decisions
Experience with software development processes, including version control, documentation, testing, and code review
Excellent technical communication skills and a customer-service mindset
Ability to work in Durham, NC (relocation assistance available)
Eligibility for US security clearance (US citizenship is required)

Preferred qualifications

Linux application development
Experience with embedded systems or deploying AI/ML solutions on edge hardware (highly desirable)
Familiarity with real-time systems, edge hardware optimization, and performance profiling
Experience with signal processing, pattern recognition, image processing, and/or machine learning techniques
Prior Department of Defense project experience

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

Software Engineer at CoVar scores 85 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.

AI Level 480 to 100
AI Level 360 to 79
AI Level 240 to 59
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

Prompt EngineeringPyTorchscikit-learn

Questions you could be asked

How do you structure and test a prompt to get consistent output from a language model?
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of scikit-learn that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Prompt Engineering, PyTorch, and scikit-learn. 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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