Lead Research Scientist - Machine Learning (Clearance Required)

As a Lead Research Scientist at STR, you will help develop disruptive technologies focused on signals exploitation, estimation theory, system resource management, and systems analysis. You will lead the development of cutting-edge AI/ML algorithms for novel application domains and modalities, participate on and lead project teams, and interact with customers. You will explore fascinating datasets, develop cutting-edge algorithmic techniques, and solve high-impact, unique problems for our customers. We are looking for someone to join our team onsite as this position is based primarily in the Woburn, MA office.

Responsibilities

Help develop disruptive technologies focused on signals exploitation, estimation theory, system resource management, and systems analysis; Lead the development of cutting-edge AI/ML algorithms for novel application domains and modalities; Participate on and lead project teams; Interact with customers; Explore fascinating datasets, develop cutting-edge algorithmic techniques, and solve high-impact, unique problems for our customers

Requirements

Active Top Secret Clearance Required with SCI eligibility, for which U.S citizenship is needed by the U.S government; MS with at least 8 years of experience, and/or PhD with at least 5 years of experience (or equivalent experience) in a scientific field such as applied math, physics, electrical engineering, computer science, or data science; Experience building neural networks using standard deep learning tools (e.g., PyTorch, JAX, TensorFlow), including implementing new layers/network architectures, model training, hyperparameter tuning, and ablation studies; Experience adapting novel machine learning approaches (e.g., from academic literature) to new data sets and problems; Experience with standard data science tools such as scikit-learn, Pandas, and Matplotlib; Proficiency in one or more programming languages: Python, C/C++; Able to work, collaborate on, and lead multi-disciplinary teams; Able to communicate technical foundations of models and algorithms to technical and non-technical audiences; Experience in intelligence or military-related mission areas

Nice to have

Experience applying deep learning to domains other than images/text, such as time series, discrete event sequence, or geospatial; Experience with self-supervised machine learning; Expertise working with time series, geospatial, and/or spatio-temporal data