AI/ML Research Scientist

MIT Lincoln Laboratory•Lexington, MA

6d•$116,400 - $182,200

About The Position

The Artificial Intelligence Technology and Systems Group at MIT Lincoln Laboratory has over 50 years of experience developing revolutionary technologies for critical national missions. Group 52 AI Technology & Systems specializes in machine learning (ML) algorithms, technologies, and systems that extract and analyze information from multimedia data—including speech, text, images, and video. In recent years, we have significantly expanded our mission to include developing impactful ML solutions for cybersecurity in collaboration with the Nation’s top cyber organizations. As a recognized leader in both basic and applied AI/ML, our group is shaping emerging AI fields and driving the Laboratory’s efforts in AI Assurance across the Department of Defense and the Intelligence Community. We also integrate expertise in multimedia, cyber, and AI assurance to develop cutting-edge technologies for Operations in the Information Environment (OIE). A hallmark of our work is a focus on operational relevance: we design and evaluate AI/ML systems using realistic datasets and metrics, and we partner directly with intelligence analysts and cyber operators to ensure rapid transition of our technologies into real-world, mission-critical systems. This is an opportunity to apply your skills to some of the most important technical challenges of our time—while learning from and contributing to a world-class research community.

Requirements

M.S. in electrical engineering, computer science or other relevant discipline or a BS and 3 years of relevant experience.
Knowledge of artificial intelligence ideally with applications on multimedia, cyber security or adversarial machine learning / AI security experience.
Advanced AI/ML knowledge – solid graduate-level coursework or equivalent work experience in machine-learning theory, deep learning, NLP, computer-vision, graph analytics, or adversarial/AI-assurance techniques.
Ability to read, evaluate, and implement state-of-the-art research papers.
Proficient Python programming – comfortable writing clean, modular, and testable code; expert-level use of deep-learning frameworks (PyTorch, TensorFlow, etc.), data-science stacks (NumPy, pandas, SciPy, etc.), and hands-on experience with agentic/LLM-oriented toolkits (e.g., MCP).
Operating in a rapid research-to-prototype pipeline – demonstrated ability to take a cutting-edge research concept, design an experimental plan, implement a functional prototype, and iterate based on quantitative evaluation.
Software-engineering best practices – strong Git workflow (branching, pull-requests, code reviews), continuous-integration testing, environment reproducibility (e.g., conda, virtualenv).
Ability to document code, write reproducible experiment notebooks, and maintain versioned releases.
Problem-solving & analytical mindset – can decompose novel, ill-defined problems, propose multiple solution paths, and select the most promising approach based on empirical evidence.
Detail-oriented, able to multi-task, with the ability to work autonomously with minimal supervision.
Effective written and oral communication skills in technical environments, technical reports, internal wiki pages; delivers clear demo presentations and briefings to both technical audience and senior mission stakeholders.
Current TS/SCI clearance or willingness to obtain one.
Selected candidate will be subject to a pre-employment background investigation and must be able to obtain and maintain a Secret level DoD security clearance.
U.S. citizenship is required.

Nice To Haves

Experience with benchmark datasets and realistic metrics (e.g. latency, accuracy, robustness) is a plus.

Responsibilities

Design, program, and architect advanced ML methods.
Develop algorithms in speech, natural language processing, multimedia, cyber, and graph analytics.
Publish and present research at premier conferences.