Machine Learning Algorithm Developer, Assistant Staff

Key Skills

Algorithms, Bayesian networks, C Programming, C++, Deep Learning, Machine learning techniques, MATLAB Programming, OpenCV, Pandas, PyTorch, TensorRT

Job Description

The nature of threats to the U.S. homeland is continually evolving, with increasingly sophisticated adversaries and criminal networks targeting our critical infrastructure, land and maritime borders, transportation systems, and public places. Our group develops technologies that use advanced sensors, data analytics, and integrated human-machine decision making to help recognize and disrupt these threats. We specialize in collecting and processing a wide range of data types — including radar, video, imagery, text, point cloud, transactional, and body-worn sensor data — from both commercial and Laboratory-developed sensors. We often apply advanced machine learning methods to convert raw data into actionable insights about the behavior of threat actors and those who intervene to stop them. To help generate requirements for and evaluate our sensing and machine learning technologies, we use systems analysis methods that consider the operators and their environment as part of the system. Our ultimate goal is to field solutions that significantly enhance the decision-making process of analysts and operators who secure the homeland.

Machine Learning Algorithm Developer, Assistant Staff

Candidate will aid in the design, implementation, and testing of machine learning algorithms relevant to Homeland Security and Defense applications. Knowledge of state-of-the-art machine learning techniques is desired, as well as experience with the design and implementation of such methods on image, video, text, or other sensor data processing tasks. Experience with experimental design methods or flexible deployment mechanisms such as containers is also a plus. Candidate must be able to make independent contributions and clearly explain work within a team setting.

Requirements

The candidate must possess a Bachelor of Science degree in computer science, mathematics, electrical engineering, or an equivalent field. Prior exposure to machine learning algorithms, through coursework or research, is required. This includes deep learning techniques in addition to more general machine learning methods (e.g., Bayesian inference). Proficiency with Python is required, while familiarity with other development platforms like Matlab or C/C++ is considered an advantage. The candidate should also have some experience with common computer vision, natural language processing, or machine learning toolboxes (PyTorch, Pandas, OpenCV, TensorRT, libtorch, etc).

For Benefits Information, clickhttp://hrweb.mit.edu/benefits

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.