Sr 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

• Provide 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.
• 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.
• Collaborate with KRI Senior R&D Engineers/Scientists for government and industry contracts.

Requirements

• Required Education & Experience: 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.

Skills & Attributes

• Strong proficiency in Python and modern ML/AI development workflows.
• Experience with C++ and/or Java for performance-critical components is a plus.
• Demonstrated experience designing, implementing, and testing end-to-end ML/AI software systems, from data ingestion to model 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, architecture decisions, and problem decomposition.

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.
• Deep understanding of PostgreSQL/PostGIS, geospatial analytics, and large-scale spatiotemporal datasets.
• Experience designing and integrating decision-support or analytical pipelines that combine ML, graph analytics, and domain data.
• Exposure to UI or frontend development for technical applications, dashboards, or analyst-facing tools: Experience with Svelte, React, or similar modern frameworks is a plus.
• Familiarity with ML model operationalization (MLOps), experiment tracking, and reproducible research pipelines.
• Experience collaborating with multidisciplinary teams across research, engineering, and operational stakeholders.