AI/ML Research Scientist

Contribute to world-class research in artificial intelligence with real impact on national security. 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.

What You Will Do

Research on state-of-the-art algorithms in signal processing, natural language processing, graph analytics, and adversarial AI. Apply innovative methods to challenging, real-world problems. Work in a collaborative, team-oriented development environment.

Why It Might Be a Fit

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

• Ph.D. in electrical engineering, computer science, or another relevant discipline, or a Masters and 5+ years of relevant experience
• Knowledge of artificial intelligence, ideally with applications to multimedia, cyber security or adversarial machine learning/AI security experience
• Deep AI/ML experience – graduate-level (or professional) knowledge of state-of-the-art machine-learning, deep-learning, LLM/agentic AI, multimodal perception, differentiable modeling and simulation packages, graph analytics, adversarial/AI-assurance, or cyber-ML
• System analysis & problem decomposition – can translate high-level end-state requirements into a clear set of research tasks, define quantitative success metrics and measures, and produce a task-breakdown structure that aligns with program/project milestones
• Operate within a rapid research-to-prototype pipeline – demonstrable ability to turn novel algorithms and approaches into robust, reproduceable prototypes in tight timescales, around iterative refinement
• Advanced Python & ML libraries – expert-level proficiency in Python and deep-learning frameworks (PyTorch, TensorFlow, etc.), plus Huggingface ecosystem, and data science frameworks (NumPy/pandas/SciPy, etc.)
• Software-engineering best practices – strong Git workflow (branching, pull-requests, code reviews), continuous-integration testing, environment reproducibility (e.g., conda, virtualenv)
• Team and Project leadership – experience leading small research teams, assigning tasks, tracking progress, removing technical blockers, and mentoring junior staff
• Stakeholder communication – strong written and oral skills for prepping technical briefings, composing white-papers, demo presentations, and funding proposals; able to convey complex research outcomes to sponsors, senior leadership, and external partners
• Must have, or the ability to obtain a full scope Top Secret Clearance

Benefits

• Comprehensive health, dental, and vision plans
• MIT-funded pension
• Matching 401K
• Paid leave (including vacation, sick, parental, military, etc.)
• Tuition reimbursement and continuing education programs
• Mentorship programs
• A range of work-life balance options