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Machine Learning Research Scientist Jobs in Washington, DC

Senior Autonomous Systems Research Scientist

Arlington, VA ยท On-site +1

$113K - $144K/yr

Applied Machine Learning and AI: Research and implement machine learning principles, techniques ... applying scientific methods * Experience leading research projects and collaborating across ...

College of Science Classification: Research Staff 12-month Job Category: Research Staff Job Type ... Applies machine learning (ML) and artificial intelligence (AI) techniques to enhance traditional ...

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

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 ...

New

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

Showing results 21-40

Machine Learning Research Scientist information

See Washington, DC salary details

$57.2K

$147.4K

$197.1K

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

As of Aug 13, 2026, the average yearly pay for machine learning research scientist in Washington, DC is $147,370.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,800.00 and $195,900.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Research Scientist, you need a strong background in mathematics, statistics, programming (typically Python or similar), and experience with machine learning frameworks, usually supported by an advanced degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Scikit-learn, and proficiency in data handling and cloud platforms is highly valued, alongside certifications like Google Cloud ML Engineer as a plus. Innovative thinking, strong communication, and effective problem-solving skills help set exceptional researchers apart. Mastery of both technical and soft skills is essential for developing impactful models, collaborating across multidisciplinary teams, and staying ahead in this fast-evolving field.

What does a machine learning research scientist do?

As a Machine Learning Research Scientist, your typical projects may include developing novel algorithms, conducting experiments on large datasets, implementing and tuning models, and publishing research findings. Your daily responsibilities often involve coding, data analysis, reading the latest literature, collaborating with engineers and product teams, and participating in internal discussions about research direction. You may also mentor junior researchers, contribute to open-source projects, and present results at conferences or internal meetings. This role offers a dynamic work environment where continuous learning and innovative problem-solving are highly encouraged.

What is a machine learning research scientist?

A Machine Learning Research Scientist develops new algorithms and models to advance the field of artificial intelligence. They conduct experiments, analyze data, and publish research to push the boundaries of machine learning theory and applications. Their work often involves designing novel architectures, optimizing existing models, and collaborating with engineers to bring research into production. This role typically requires a deep understanding of mathematics, statistics, and programming, along with experience in areas like deep learning, reinforcement learning, or probabilistic modeling.

What are the most commonly searched types of Machine Learning Research Scientist jobs in Washington, DC?

The most popular types of Machine Learning Research Scientist jobs in Washington, DC are:

What job categories do people searching Machine Learning Research Scientist jobs in Washington, DC look for?

The top searched job categories for Machine Learning Research Scientist jobs in Washington, DC are:

Infographic showing various Machine Learning Research Scientist job openings in Washington, DC as of August 2026, with employment types broken down into 71% Full Time, and 29% Part Time. Highlights an 66% In-person, and 34% Remote job distribution, with an average salary of $147,370 per year, or $70.9 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 13 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.