Senior Research Scientist

About the Opportunity

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 include providing technical contributions as a software engineer for a wide range of projects involving machine learning (ML) and artificial intelligence (AI), including autonomy, sensing and communication, and decision support systems, among others. The R&D Engineer will work collaboratively with multi-disciplinary teams across the KRI consortium, consisting of academic and industry partners, to create solutions and prototypes for projects in application areas, including autonomous systems, robotics, cognitive and distributed sensing, and machine learning systems, among others.

Successful candidates will be responsible team players and passionate about machine learning technologies, as well as possess a deep understanding of machine learning technology and experience in turning machine learning technologies into practical, state-of-the-art systems. A close working relationship with and support of KRI Senior R&D Engineers/Scientists for government and industry contracts will be required.

The Kostas Research Institute was founded with a focus on homeland security research and development. Today, KRI strives to advance resilience in the face of 21st century risks across a wide range of technologies, emphasizing a collaborative approach that leverages our R1 university intellectual capital and technologies to develop application-specific solutions to customer needs. KRI focuses on satisfying customer-driven needs by co-locating a diverse, highly skilled R&D team that can address all aspects of a particular problem across the full range of technology-readiness levels. KRI headquarters, located at the NU Innovation Campus in Burlington, MA (ICBM), is home to one-of-a-kind research and test facilities for conducting activities related to cognitive and distributed RF signal processing and machine learning, unmanned and autonomous system technologies, as well as quantum materials and sensing.

This position is with KRI at Northeastern University, LLC, a wholly-owned subsidiary of NU. The primary office for this position is located at NU's ICBM. Through NU, KRI offers an impressive benefits package, including multiple retirement plan options with extremely generous matching, as well as tuition waiver for classes and advanced degree programs. A full description of available benefits can be found on the NU website.

Education & Experience

Required

• Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Applied Mathematics, or a closely related field.
• 5+ years of professional experience in software engineering with a strong focus on machine learning and AI systems development (research, applied R&D, or production environments).

Preferred

• Advanced degree (M.S. or Ph.D.) with applied ML/AI, network science, optimization, or data-intensive systems focus.
• Experience supporting government, defense, or security-related R&D programs.
• Experience developing or integrating simulation-based models, including physics-based, network-based, agent-based, or stochastic simulations for system analysis, experimentation, or decision support.

Skills & Attributes

Required

• Strong proficiency in Python and modern ML/AI development workflow.
• Experience with C++ and/or Java for performance-critical components is a plus.
• Demonstrated experience designing, implementing, and testing end-to-end ML/AI and/or simulation-driven software systems, from data ingestion and model development to experimentation and deployment.
• Hands-on experience with machine learning frameworks, particularly PyTorch, including model training, fine-tuning, evaluation, and experimentation.
• Experience working in high-performance computing (HPC), distributed compute, or accelerated environments (GPUs, multi-node systems).
• Solid background in database systems, including: Relational databases (e.g., PostgreSQL / SQL), Graph databases (e.g., Neo4j, Memgraph, or equivalent)
• Familiarity with cloud computing environments (e.g., Azure, AWS, or GovCloud equivalents), including containerized or scalable ML workflows.
• Strong software engineering fundamentals: version control, modular design, testing, documentation, and reproducibility.
• Proven ability to rapidly prototype novel solutions and transition them toward robust, deployable systems.
• Self-motivated team member capable of contributing to technical planning, system architecture decisions, and problem decomposition.
• U.S. Citizenship with the ability to obtain and maintain a security clearance.

Desired Skills & Attributes

• Experience with Retrieval-Augmented Generation (RAG) architectures, vector databases, embedding pipelines, and LLM-integrated systems.
• Strong background in network science and graph analytics, including: Graph modeling and analysis using tools such as NetworkX, Graph-based ML or graph neural networks (GNNs) is a plus
• Experience with modeling and simulation techniques, such as: Network, agent-based, or discrete-event simulation, Monte Carlo or stochastic simulation methods, Simulation-in-the-loop (SiL) or synthetic data generation to support ML training and evaluation
• Experience integrating simulation outputs with ML models, decision-support systems, or analytical pipelines.
• Deep understanding of PostgreSQL/PostGIS, geospatial analytics, and large-scale spatiotemporal datasets.
• Exposure to UI or frontend development for technical applications, dashboards, or analyst-facing tools (e.g., Svelte, React, or similar frameworks).
• Familiarity with MLOps practices, experiment tracking, and reproducible research pipelines.
• Experience collaborating with multidisciplinary teams across research, engineering, and operational stakeholders.
• Security clearance.

Key Responsibilities & Accountabilities:

Software R&D activities, including software development and 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%)