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Job Description
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. Skills & Attributes Required 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., Postgre
SQL / 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. 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 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. Position Type Research Additional Information Northeastern University considers factors such as candidate work experience, education and skills when extending an offer. Northeastern has a comprehensive benefits package for benefit eligible employees. This includes medical, vision, dental, paid time off, tuition assistance, wellness & life, retirement- as well as commuting & transportation.
Visit https:
//hr.northeastern.edu/benefits/ for more information. 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.
Compensation Grade/Pay Type:
113
S Expected Hiring Range:
$113,865.00 - $165,105.00 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. Founded in 1898, Northeastern is a global research university and the recognized leader in experiential lifelong learning. Our approach of integrating real-world experience with education, research, and innovation empowers our students, faculty, alumni, and partners to create worldwide impact. Our global university system provides our community and academic, government, and industry partners with unique opportunities to think locally and act globally. The system—which includes 14 campuses across the U.S., U.K., and Canada, 300,000-plus alumni, and 3,000 partners worldwide—serves as a platform for scaling ideas, talent, and solutions. The university's residential campuses for undergraduate and graduate degrees are located in Boston, London, and Oakland, California. Our research and graduate campuses are in the Massachusetts communities of Burlington and Nahant; Arlington, Virginia; Charlotte, North Carolina; Miami; Portland, Maine; Seattle; Silicon Valley, California; Toronto; and Vancouver. Northeastern's personalized, experiential undergraduate and graduate programs lead to degrees through the doctorate in 10 colleges and schools across our campuses. Learning emphasizes the intersection of data, technology, and human literacies, uniquely preparing graduates for careers of the future and lives of fulfillment and accomplishment. Our research enterprise, with an R1 Carnegie classification, is solutions oriented and spans the world. Our faculty scholars and students work in teams that cross not just disciplines, but also sectors—aligned around solving today's highly interconnected global challenges and focused on transformative impact for humankind.
