Research Scientist

About the Opportunity This job description is intended to describe the general nature and level of work being performed by people assigned to this classification. It is not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Job Summary The Kostas Research Institute (KRI) at Northeastern University (NU) – a rapidly growing institute that conducts cutting‑edge applied R&D – is seeking a highly motivated, experienced and enthusiastic Research & Development (R&D) Engineer with expertise in ML&AI. The R&D Engineer is expected to work as part of a multi‑disciplinary team and contribute to the successful execution of R&D projects. Responsibilities Provide technical contributions as a software engineer for a wide range of projects involving machine learning (ML) and artificial intelligence (AI), including autonomy, sensing, communication, and decision support systems. Work collaboratively with multi‑disciplinary teams across the KRI consortium to create solutions and prototypes for projects in autonomous systems, robotics, cognitive and distributed sensing, and machine learning systems. Be a responsible team player passionate about machine learning technologies, possess a deep understanding of machine learning technology, and have experience turning machine learning technologies into practical, state‑of‑the‑art systems. Maintain a close working relationship with and support KRI Senior R&D Engineers/Scientists for government and industry contracts. Education & Experience Required Bachelor’s or Master’s degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, or a closely related field. 2–4 years of professional experience in software engineering, data science, or applied R&D, with exposure to machine learning and AI system development in research, prototype, or production environments. Preferred Master’s degree with a focus on ML/AI, data‑intensive systems, network science, optimization, or related areas. Experience contributing to government, defense, or security‑related R&D programs (internships, fellowships, or full‑time roles). Familiarity with simulation‑based models (physics‑based, network‑based, agent‑based, or stochastic simulations) for analysis, experimentation, or decision support. Skills & Attributes Required Proficiency in Python and familiarity with modern ML/AI development workflows. Exposure to C++ and/or Java for performance‑critical components is a plus. Experience contributing to the design, implementation, testing, or evaluation of ML/AI‑enabled or simulation‑driven software systems. Hands‑on experience with machine learning frameworks (e.g., PyTorch), including model training, evaluation, and experimentation. Familiarity with distributed or accelerated computing environments (GPU‑enabled systems, shared compute clusters). Working knowledge of database systems, including relational databases (PostgreSQL/SQL), exposure to graph databases (Neo4j, Memgraph, or similar), and familiarity with cloud computing environments (Azure, AWS, or GovCloud equivalents). Experience with containerized or scalable ML workflows is a plus. Solid software engineering fundamentals: version control, modular code design, testing, documentation, and reproducibility. Ability to rapidly prototype solutions and iterate toward more robust implementations with guidance from senior engineers. Self‑motivated team member able to work independently on well‑defined tasks while contributing to broader project objectives. U.S. Citizenship with the ability to obtain and maintain a security clearance. Desired Skills & Attributes Exposure to Retrieval‑Augmented Generation (RAG), vector databases, embedding pipelines, or LLM‑enabled systems. Familiarity with network science or graph analytics concepts: Graph modeling and analysis using NetworkX; introductory experience with graph‑based ML or GNNs is a plus. Experience or coursework involving modeling and simulation techniques such as network, agent‑based, or discrete‑event simulation; Monte Carlo or stochastic simulation methods; synthetic data generation or simulation‑in‑the‑loop workflows; exposure to geospatial data, spatiotemporal datasets, or PostgreSQL/PostGIS is a plus. Interest in UI or frontend development for technical or analyst‑facing tools (Svelte, React, or similar frameworks). Familiarity with MLOps concepts, experiment tracking, or reproducible research pipelines. Experience working with multidisciplinary teams across research, engineering, and applied R&D environments. Active security clearance is a plus. Key Responsibilities & Accountabilities Software R&D activities: software development, implementation, prototype modeling & simulation, design, and experimentation (45%). Test and validation of software systems and software for prototype deployment (45%). Provide software development subject matter expertise across a diverse set of application areas and contribute to proposals, publications, whitepapers, etc. (10%). Position Type Research Compensation Grade/Pay Type 110S Expected Hiring Range $76,335.00 - $107,823.75 With the pay range(s) shown above, the starting salary will depend on several factors, which may include your education, experience, location, knowledge and expertise, and skills as well as a pay comparison to similarly‑situated employees already in the role. Salary ranges are reviewed regularly and are subject to change. All qualified applicants are encouraged to apply and will receive consideration for employment without regard to race, religion, color, national origin, age, sex, sexual orientation, disability status, or any other characteristic protected by applicable law. #J-18808-Ljbffr