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Machine Learning Research Engineer Jobs in Virginia

Machine Learning Engineer LOCATION Chantilly, VA 20151 CLEARANCE TS/SCI Full Poly (Please note this ... Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Machine Learning Engineer

Reston, VA ยท On-site

$110 - $170/hr

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Machine Learning Engineer LOCATION Reston, VA 20190 CLEARANCE TS/SCI Full Poly (Please note this ... Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Machine Learning Engineer LOCATION Tysons, VA 22182 CLEARANCE TS/SCI Full Poly (Please note this ... Engineer, Research Scientist, Data Engineer, NLP Engineer, Computer Vision Engineer, AI/ML ...

Machine Learning Engineer

Chantilly, VA ยท On-site

$140 - $190/hr

Careers At Elder Research Current job opportunities are posted here as they become available ... Machine Learning Engineer to join our team in Chantilly, VA. Build and deploy AI agents to both ...

... data scientist, machine learning engineer, or similar role * Solid understanding of the ... Generous pay * Cutting edge research opportunities * Competitive medical benefits * Flexible ...

Machine Learning Engineer

Chantilly, VA ยท On-site

$140 - $180/hr

Careers At Elder Research Current job opportunities are posted here as they become available ... Machine Learning Engineer to join our team in Chantilly, VA. Build and deploy AI agents to both ...

Machine Learning Researcher

Broadway, VA ยท On-site

$154K - $213K/yr

Morgan Stanley's Machine Learning Research Department is responsible for working across the Firms many business units and technology teams to solve mission-critical problems. We are a highly ...

Machine Learning Engineer

Arlington, VA ยท Hybrid

$110K - $160K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Machine Learning Engineer

Arlington, VA ยท Hybrid

$110K - $160K/yr

Kitware is a leader in advanced research and algorithm development in artificial intelligence (AI ... Machine learning experience using visual data * Understanding of a variety of machine learning ...

Showing results 21-40

Machine Learning Research Engineer information

See Virginia salary details

$36.7K

$105.1K

$141.3K

How much do machine learning research engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning research engineer in Virginia is $105,103.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,100.00 and $103,100.00 per year, depending on experience, location, and employer.

What does a machine learning research engineer do?

A Machine Learning Research Engineer develops and improves machine learning models, conducts research to advance AI techniques, and implements scalable algorithms. They work at the intersection of applied research and engineering, leveraging mathematical and statistical methods to optimize performance. Their role involves experimenting with new architectures, analyzing large datasets, and collaborating with data scientists and software engineers to deploy models into production.

What are the key skills and qualifications needed to thrive as a machine learning research engineer?

A Machine Learning Research Engineer typically needs a strong background in computer science, mathematics, and statistics, often with a graduate degree in a related field. Proficiency in programming languages such as Python or C++, experience with machine learning frameworks like TensorFlow or PyTorch, and familiarity with tools for data analysis are crucial, along with relevant certifications being a plus. Strong problem-solving skills, collaboration, and effective communication help drive innovative research and facilitate teamwork. These competencies are essential for developing advanced machine learning models, staying current with evolving technologies, and effectively translating research into real-world applications.

What are some common challenges faced by machine learning research engineers in their daily work?

Machine Learning Research Engineers often encounter challenges such as sourcing and preparing large, high-quality datasets, tuning complex model architectures, and ensuring reproducibility of experimental results. They work closely with cross-functional teams, including data scientists and software engineers, to deploy models in production environments and must frequently adapt to rapidly evolving research. Keeping up with the latest scientific literature and integrating new algorithms into ongoing projects can be demanding but is also rewarding. This collaborative, fast-paced environment provides constant opportunities for learning and professional development.

What are popular job titles related to Machine Learning Research Engineer jobs in Virginia?

For Machine Learning Research Engineer jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Research Engineer jobs in Virginia look for?

The top searched job categories for Machine Learning Research Engineer jobs in Virginia are:

Infographic showing various Machine Learning Research Engineer job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 28% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $105,103 per year, or $50.5 per hour.

Senior Machine Learning Research Scientist - Frontier Lab

Software Engineering Institute | Carnegie Mellon University

Arlington, VA โ€ข On-site

$113K - $144K/yr

Full-time

Re-posted 22 days ago


Job description

Job Summary:
Carnegie Mellon University is conducting research in applied artificial intelligence through its SEI AI Division. The Senior Machine Learning Research Scientist will lead applied research and prototype development for government missions, collaborating across research and engineering disciplines while ensuring technical execution aligns with mission needs.
Responsibilities:
โ€ข Execute work within the operational contextโ€”understanding users, workflows, constraints, success criteria, and outcomesโ€”so technical decisions are grounded in real mission needs.
โ€ข Lead technical execution by defining technical tasking, sequencing work into realistic milestones, maintaining delivery quality, and delegating appropriately across the team.
โ€ข Design and run studies, build convincing prototypes and reference implementations, and produce evidence-backed insights that can be matured and transitioned into operational settings.
โ€ข Establish credible evaluation strategies and test pipelines that assess performance, robustness, reliability, and trustworthiness in mission-representative scenarios.
โ€ข Serve as the primary technical interface when appropriate; translate mission goals into measurable technical outcomes; communicate progress, decisions, and risks clearly to stakeholders.
โ€ข Proactively mentor junior staff and teammates, raising the bar for research rigor, engineering practice, and delivery habits across project teams.
โ€ข Maintain strong awareness of frontier developments aligned to the Frontier Lab, share insights with the lab, and help shape research directions and future work selection.
โ€ข Manage multiple priorities effectively, sustain steady execution cadence, and resolve blockers with minimal oversight.
โ€ข Build a strong research culture through internal talks, reading groups, and workshops; and engage with external AI/ML communities (professional societies, consortiums, working groups, and conferences) to strengthen collaboration pathways and keep the lab connected to emerging practice.
Qualifications:
Required:
โ€ข BS in Computer Science, Electrical Engineering, Statistics, or related field with 10 years of relevant experience; OR MS with 8 years of relevant experience; OR PhD with 5 years of relevant experience.
โ€ข Deep expertise in one or more Frontier Lab-aligned areas (agentic systems, LLM reliability/evaluation, CV evaluation, robustness/assurance, TEVV pipelines, multimodal learning, edge ML).
โ€ข Strong engineering capability โ€“ can build and maintain high-quality prototypes, evaluation infrastructure, and repeatable experimentation workflows.
โ€ข Strong written and verbal communication skills; able to represent technical work credibly to senior stakeholders.
โ€ข Demonstrated ability to lead technical workstreams and coordinate multi-person execution.
โ€ข Flexible to travel to SEI offices in Pittsburgh, PA and Washington, DC / Arlington, VA, sponsor sites, conferences, and offsite meetings (~10% travel).
โ€ข You must be able and willing to work onsite at an SEI office in Pittsburgh, PA or Arlington, VA 5 days per week.
โ€ข You will be subject to a background investigation and must be eligible to obtain and maintain a Department of War security clearance.
Preferred:
โ€ข Leading applied research projects resulting in effective prototypes, mission-relevant evaluation outcomes, or transitioned methods.
โ€ข Publications at strong venues (e.g., NeurIPS / ICLR / ICML, relevant workshops, MLCON), and/or demonstrable impact through applied research artifacts (benchmarks, evaluation suites, open-source, technical reports).
โ€ข Designing and operating TEVV efforts including evaluation pipelines, robustness analysis, calibration/uncertainty work, regression suites, and scenario-based evaluation protocols.
โ€ข Building agentic capabilities integrated with tools, data systems, and human workflows (decision support, planning, analytic contexts).
โ€ข Experience with secure or operational environments and delivery constraints typical of government settings.
โ€ข Experience shaping a technical roadmap or research portfolio aligned to sponsor priorities and lab strategy.
Company:
We conduct cutting-edge research and development that accelerates the transition of technology to the Department of War (DoW), delivering measurable impact in support of the national security mission. Founded in 1984, the company is headquartered in Pittsburgh, USA, with a team of 501-1000 employees. The company is currently Late Stage.