AI/ML Engineer - Assistant Staff

MIT Lincoln Laboratory•Lexington, MA

2d•$100,200 - $150,000

About The Position

The Advanced Concepts & Technologies Group (Group 39) is looking for exceptional engineers, scientists, and mathematicians who are excited to solve challenging problems. To improve operational effectiveness in rapidly evolving, complex threat environments, Group 39 conducts cutting-edge research and development in systems and architecture analysis; modeling and simulation; software and hardware prototyping and fielding; artificial intelligence; and signal processing. The group’s multidisciplinary team includes scientists and engineers with backgrounds in physics, mathematics, computer science, and engineering. Group 39 values inclusiveness, fosters mentoring at all levels, and promotes critical and innovative thinking to address the needs of the nation. The successful candidate will join a highly collaborative team that supports professional growth and is dedicated to solving important national security challenges. The Advanced Concepts and Technologies Group is seeking an Assistant Staff candidate to develop and apply artificial intelligence, modeling, and data-analysis methods for technology development and assessment. Our team works with government sponsors to understand complex operational and technical problems, develop new capabilities, and quantitatively evaluate emerging technologies and concepts. The successful candidate will contribute to efforts spanning algorithm and software development, modeling, experimentation, and analysis. Working with experienced technical staff, mission subject-matter experts, scientists, and engineers, the candidate will help translate technical and operational questions into software capabilities, models, experiments, and quantitative assessments. Work may involve deep learning, large language models, logic models, reinforcement learning, applied statistics, physics-based modeling, and analysis of complex structured and unstructured datasets. Depending on the problem, these methods may be applied through simulation, interactive environments, experimental prototypes, or other analysis tools.

Requirements

Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Applied Mathematics, Physics, Engineering, Operations Research, or a related technical field.
Demonstrated programming ability in Julia, Python, or a similar scientific programming language.
Coursework, research, internship, or project experience in artificial intelligence, machine learning, or computational decision modeling, including practical experience in at least one of the following areas: deep learning, large language models, logic models, or reinforcement learning.
Demonstrated problem-solving ability and experience developing software, models, algorithms, or analytical capabilities.
Basic knowledge of applied statistics and quantitative methods, including experience interpreting analytical results.
Experience working with structured, poorly structured, or unstructured datasets.
Strong written and oral technical communication skills, including the ability to clearly explain technical concepts, methods, and results.
Ability to work effectively both independently with direction and as part of a collaborative, multidisciplinary team.
Ability to rapidly learn new technical and mission areas.

Nice To Haves

Software engineering experience, including modular software design, automated testing, version control, code review, and technical documentation.
Experience applying AI/ML, modeling, or data analysis to technology development, system assessment, or decision support.
Experience with formal or logic-based modeling approaches, such as PDDL, signal temporal logic, automated planning, rule-based systems, or related methods.
Experience developing visualizations, user interfaces, or interactive tools for complex technical systems, including simulations, analytical applications, or serious games.
Familiarity with Department of War missions, operations, systems, or technologies.
Background in physics-based modeling, particularly radar systems, sensor performance, detection, tracking, or radio-frequency propagation.
Experience with Monte Carlo simulation, experimental design, uncertainty quantification, and/or sensitivity analysis.
Experience with agent-based models, decision-support tools, human-machine teaming, or autonomous decision-making systems.
Experience with high-performance, parallel, distributed, or GPU computing.
Experience working on collaborative research or software development projects.
Active Secret clearance.

Responsibilities

Develop and apply AI, modeling, or analysis capabilities for technology development and assessment.
Work with technical staff and subject-matter experts to translate operational and technical questions into quantitative analyses, models, and evaluation approaches.
Develop and evaluate AI/ML methods using deep learning, large language models, logic models, reinforcement learning, or related techniques.
Develop and integrate statistical, physics-based, and data-driven models of complex systems and operations.
Conduct quantitative studies and experiments, analyze complex structured and unstructured datasets, and extract meaningful technical and operational insights.
Develop software prototypes and analysis tools and contribute to testing, verification, validation, documentation, version control, and code review.
Collaborate with multidisciplinary teams and rapidly learn new technical and mission areas.
Communicate technical methods, assumptions, limitations, and results through clear documentation, demonstrations, and briefings.