Machine Learning Developer

Job Overview

MIT Lincoln Laboratory Technical Staff provide critical through expert multi-domain or new-domain innovative research supporting the Laboratory’s national security mission. They prototype state-of-the-art technology solutions and engage across the program lifecycle, leading projects or major/multiple technical workstreams in partnership with project, program and team/Group leaders. As a Technical Staff member, you will lead complex technical efforts requiring deep expertise, sound judgment, with the ability to successfully navigate technical complexity. Depending on the level, you will lead projects, major workstreams, complex programs, multi-program initiatives, or technical portfolios on extraordinary technology prototype efforts and creative new ideas and approaches that support critical mission needs. Depending on the level, you will translate broad Group strategy into clearly defined research or executional deliverables. Through integrating your deep technical expertise across disciplines, you consistently drive high-quality mission outcomes. 

As a successful candidate, you will connect deep and diverse technical expertise with broader Laboratory objectives, perform independent research, develop creative approaches, and translate broad strategy into executable plans. You will work across or guide multidisciplinary teams through ambiguous trade-offs; helping develop and execute programs, creating briefings and reports, and often interfacing with sponsors. You effectively support sponsor, mission-partner, and Laboratory leadership’s needs through daily or weekly technical briefings, program documentation, proposals, and may conduct advanced capability road mapping and development. You will also guide and mentor Associate Technical Staff, Assistant Technical Staff, and other technical support personnel. 

Job Duties & Responsibilities

We are looking for applicants with an interest and background in applied engineering, modeling and simulation and machine learning to develop algorithms and systems for autonomous and semi-autonomous vehicles. Additionally, we are looking for applicants to develop new advanced decision support systems as well as architectures and techniques for advancing and deploying semi-autonomous systems in the broader transportation domain. Example problem areas include algorithm development for collision avoidance logic, real-time contingency management, inter-vehicle coordination, and validation of decision support, surveillance, and tracking systems. Successful candidates will develop the skills to analyze the operational problems in detail and to develop deployable solutions, while extending our impact to other areas of the transportation domain.  The candidate should be familiar with developing solutions using modern machine learning approaches such as reinforcement learning. Additional responsibilities include leading and developing applied research and development programs in the transportation domain, formulating new approaches to existing challenges and publishing results in conferences/journals. The Transportation Safety and Resilience Group supports a hybrid work environment.

Minimum Qualifications

Candidates will be considered for the appropriate level based on their education, experience, demonstrated technical expertise and breadth, leadership responsibilities, and the scale and complexity of programs or technical efforts they have led. 

Level 5 – Technical Staff 

• Bachelor’s degree in a STEM discipline or other relevant technical field and typically 6+ years of relevant experience; or Master’s degree and typically 4+ years of relevant experience; or PhD and typically 0+ years of relevant experience; or an equivalent combination of education and experience. 
• Diverse technical expertise with demonstrated ability to adapt that expertise to unfamiliar or emerging disciplines, systems, mission areas, or methods. 
• Established education, skills, and experience demonstrating the ability to apply significant technical judgment to broad challenges requiring integration across related systems or methods. 
• Demonstrated ability to lead projects or major workstreams and deliver complex technical outcomes. 
• Experience evaluating trade-offs, recommending paths forward, and adapting technical approaches to evolving project needs. 
• Demonstrated mentorship, collaboration, and ability to communicate recommendations, risks, and technical findings to varied audiences. 
• Experience contributing to technical reports, papers, presentations, proposals, or other formal technical deliverables. 

Level 6 – Technical Staff 

• Bachelor’s degree in a STEM discipline or other relevant technical field and typically 8+ years of relevant experience; or Master’s degree and typically 6+ years of relevant experience; or PhD and typically 2+ years of relevant experience; or an equivalent combination of education and experience. 
• Deep and diverse technical expertise with demonstrated ability to integrate knowledge across domains and establish direction in evolving systems or mission areas. 
• Established education, skills, and experience demonstrating the ability to incorporate technical judgment, program context, and stakeholder input to solve broad technical challenges. 
• Proven experience leading complex programs, significant program elements, or multi-team technical efforts. 
• Demonstrated ability to evaluate alternatives, manage technical ambiguity, and influence decisions across teams or stakeholder groups. 
• Strong record of mentorship, collaboration, technical communication, and contribution to team or Group capability development. 
• Experience contributing to proposals, publications, technical reports, presentations, or other materials that shape program direction or technical initiatives. 

Additional Minimum Qualifications

•          PhD in engineering, physics, Mathematics, or computer science or similar field; in lieu of a PhD, a Master’s degree with four years of relevant experience will be considered.

•          Experience with state of the art machine learning approaches and architectures

•          Experience developing algorithms and architectures for advancement and deployment of autonomous systems

•          Experience with reinforcement learning

•          Publication record with conference and/or journal articles

•          Experience with algorithmic software development in Python

•          Ability to collaborate well as part of a team with good interpersonal skills

•          Ability to effectively distill and distribute concepts and results to a wide audience

Preferred Qualifications

•          Knowledge of the air or surface transportation domain

•          Experience developing algorithms and/or mathematical models in a simulation environment and/or deploying and testing on hardware

•          Experience with Natural Language Processing, Natural Language Understanding or Automatic Speech Recognition

•          Experience in other programming languages such as Python, C++, MATLAB, Julia, etc.

•          Publications in (air) transportation related conferences/journals

•          Experience leading a small team

•          Experience with distributed computing and scalable machine learning frameworks

Experience submitting research proposals