Interested in this Research Scientist role at MIT Lincoln Laboratory?
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The Secure Resilient Systems and Technology group advances cybersecurity research to address critical national security challenges. We develop and evaluate technologies that enable mission systems, from space and autonomous platforms to tactical communications and secure computing, to withstand cyberattack and continue the mission. Our goal is not simply to identify vulnerabilities, but to design security in from the start and provide rigorous evidence that these systems can be trusted under attack.
Our research spans secure software and embedded systems, security architecture and threat modeling, applied cryptography, formal methods, and security evaluation. It increasingly includes the intersection of AI and cybersecurity, both using AI to advance cybersecurity and securing AI-enabled mission systems. We work across the R&D lifecycle, from new concepts through prototyping and transition to mission use, collaborating across Lincoln Laboratory and with government, industry, and academia. We maintain a strong focus on mission impact. As a result, our work spans multiple levels of sensitivity; whenever possible, we publish portions of our research and engage with the broader academic community.
We are a collegial and mission-driven team working on difficult problems where security, resilience, assurance, performance, and operational realities all matter. We value technical excellence, innovation, collaboration, inclusion, and individual growth. Our culture emphasizes mentoring and developing researchers into PIs and technical leaders. We strive to bring out the best in our people and our systems, so that the Laboratory and the nation can count on them when it matters most.
If you would like to pursue cutting-edge research and work on things that truly matter at a place that combines MIT's culture of academic excellence, exceptional resources, and strong work-life balance, apply here to learn more.
Job Description
As a Full Technical Staff member, you will:
- Advance the state of the art in cybersecurity by developing and evaluating new approaches to securing software, embedded systems, communications, and computing infrastructure against sophisticated cyber threats.
- Shape research directions and lead technically challenging R&D efforts, from new concepts through prototyping, evaluation, and transition to mission use.
- Pursue research at the intersection of AI and cybersecurity, including applications of AI to cyber analysis and defense, as well as the security and evaluation of AI-enabled systems.
- Publish and present research and collaborate with researchers across Lincoln Laboratory, government, industry, and academia.
- Mentor researchers and engineers, identify important new problems, and contribute to the development of new research programs and sponsor relationships.
Required Qualifications
To thrive in this role, you should have:
- A PhD in Computer Science, Computer Engineering, Cybersecurity, Software Engineering, Systems Engineering, or a closely related computing or engineering field.
+ Alternatively, a Master's degree with at least five years of relevant professional or research experience. + Candidates whose prior degrees are in another technical field may qualify with substantial relevant professional or research experience demonstrating comparable technical preparation.
- Demonstrated technical depth in one or more of the following: + Systems security, particularly for embedded systems. + Software security and program analysis. + Secure-by-design systems and architectures. + Applied cryptography and security protocols. + Software testing, metrics, and evaluation. + Applied formal methods and programming languages security. + AI-enabled tools and techniques for cybersecurity.
- A record of research or technical innovation, demonstrated through publications, patents, significant technical projects, prototypes, or comparable contributions that address complex problems with new approaches.
- Demonstrated technical initiative and potential to lead research efforts, including the ability to identify important problems, formulate technical approaches, and influence the direction of collaborative work.
- Strong technical communication skills, including the ability to communicate complex ideas effectively to technical and nontechnical audiences.
Desired Experience and Expertise
We particularly value demonstrated experience in one or more of the following areas:
- Secure software development, operating system internals, embedded systems security, and network protocols.
- Systems engineering, security requirements analysis, and threat modeling.
- Security evaluation and assurance, including adversarial testing, experimental methods, security measurement, and evidence supporting security and assurance claims.
- Applied cryptography and protocols, including industry and government standards.
- Static and dynamic software analysis and applied formal methods.
- AI-enabled software analysis, vulnerability discovery, security testing, threat analysis, and cyber defense.
- Security and evaluation of AI-enabled systems, including adversarial threats, robustness, and resilience.
- Experience across the R&D lifecycle, from concept development and prototyping through evaluation and transition, particularly in national security, government, or defense-related environments.
- Systems-level thinking and analysis, including identifying important national security problems, understanding mission and technical context, evaluating alternative approaches and tradeoffs, and translating technical vision into executable research plans.
- Technical leadership and mentoring of researchers and engineers.
- Development of new research concepts, proposals, or programs, including collaboration with government sponsors and other research partners.
We do not expect candidates to have expertise in all of these areas.
Recent Graduate Hiring Range: $145,200 - $170,000
Experienced Hiring Range: $145,200 - $220,000
Disclaimer: MIT Lincoln Laboratory provides a typical hiring range as a good faith estimate of what we reasonably expect to offer for this position at the time of posting. The final salary offered to a selected candidate will depend on various factors, including—but not limited to—the scope and responsibilities of the role, the candidate’s experience, skills and education/training, internal equity considerations and applicable legal requirements. This range reflects base salary only and does not include additional forms of compensation or benefits.
At MIT Lincoln Laboratory, our exceptional career opportunities include many outstanding benefits to help you stay healthy, feel supported, and enjoy a fulfilling work-life balance. Benefits offered to employees include:
- 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
- ... and much more!
Please visit our Benefits page for more information. As an employee of MIT, you can also take advantage of other voluntary benefits, discounts and perks.
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.
MIT Lincoln Laboratory is an Equal Employment Opportunity (EEO) employer. All qualified applicants will receive consideration for employment and will not be discriminated against on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, age, veteran status, disability status, or genetic information; U.S. citizenship is required.
Requisition ID: 43409
Salary Context
This $145K-$220K range is below the median for Research Scientist roles in our dataset (median: $197K across 73 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 8,943 AI roles we're tracking, Research Scientist positions make up 2% of the market. At MIT Lincoln Laboratory, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills in Demand for This Role
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 708 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200. This role's midpoint ($182K) sits 18% below the category median. Disclosed range: $145K to $220K.
Across all AI roles, the market median is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,250; VP: $235,000.
MIT Lincoln Laboratory AI Hiring
MIT Lincoln Laboratory has 4 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer, Research Engineer. Positions span Lexington, MA, US, Lexington, MA. Compensation range: $150K - $220K.
Location Context
Across all AI roles, 6% (521 positions) offer remote work, while 8,351 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,416 roles, $263,811 median); Los Angeles (1,340 roles, $210,000 median).
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 8,943 open positions tracked in our dataset. By seniority: 175 entry-level, 4,132 mid-level, 3,268 senior, and 1,368 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (521 positions). The remaining 8,351 roles require on-site or hybrid attendance.
The market median for AI roles is $213,380. Top-quartile compensation starts at $264,148. The 90th percentile reaches $319,310. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 8,943 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,739), AI Product Manager (403), AI Software Engineer (402). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (175) are outnumbered by mid-level (4,132) and senior (3,268) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 1,368 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (521 positions), with 8,351 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $213,380. Top-quartile roles start at $264,148, and the 90th percentile reaches $319,310. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $253,100 median, while Prompt Engineer roles sit at $141,440. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,422 postings), Aws (808 postings), Azure (638 postings), Rag (555 postings), Gcp (457 postings), Pytorch (433 postings), Claude (341 postings), Kubernetes (337 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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