The Kempner Institute for the Study of Natural and Artificial Intelligence, a new non-profit research institute at Harvard University, is a dynamic and diverse community of students, scientists, and engineers dedicated to unraveling the basis of intelligence in both natural and artificial contexts and leveraging these findings to develop groundbreaking technologies. To support this growing community of scientists and students, the Kempner Institute is establishing one of the largest academic machine-learning supercomputers in the world. Additionally, the institute is hiring senior engineers with deep experience in machine learning and AI to facilitate cutting-edge research.
We are hiring a Senior ML Research Engineer with a proven record of technical leadership and solid engineering skills to enhance our engineering team at the Kempner Institute. The Senior ML Research Engineer will play a critical role in assisting researchers by writing robust machine-learning code, implementing software engineering best practices, optimizing AI/ML HPC workflows on a GPU cluster, disseminating code on open science platforms as open-source software, building distributed AI/ML software infrastructure, supporting research on AI/ML and science behind next-generation algorithms, utilizing their expertise to tackle complex challenges in large AI/ML applications, and providing essential training and guidance in these domains.
This position operates within a team of senior engineers and reports to the Director of Engineering. The ideal candidate will demonstrate a passion for pushing the boundaries of AI/ML technologies and an enthusiasm to contribute to a collaborative and innovative environment. Harvard University encourages candidates with diverse backgrounds and fresh perspectives to join the Kempner Institute.
Summary Design, plan, and implement software and data services that support and enrich research productivity and reliability. Develop software and data services with researchers to ensure that modern standards of reproducible research are kept.
Advise researchers in the design, planning, and implementation of software or data analysis that enriches research productivity and reliability
Build deep understanding of specific research activities through regular engagements
Develop a scope of work and timely project plan with regular milestones
Build and maintain software code and custom data processing pipelines for complex environments
Apply firm understanding of numerical methods or data analysis to develop custom solutions to meet researchers' needs
Work in a team of developers and researchers in collaboration with systems professionals
Provide regular communications to stakeholders with project updates
Build internal code design and development guides for future contributors
Build advanced curriculum and teach workshops for researchers on sustainable software and data management practices that preserve the reproducibility of their research domain
Abide by and follow the Harvard University IT technical standards, policies and Code of Conduct
Candidates MUST meet the following basic qualifications to be considered for this role:
Minimum of seven years post-secondary education or relevant work experience (can be a combination of education and work experience).
Additional Qualifications and Skills
Additional Qualifications and Skills
Expertise in implementing software engineering best practices such as code reviews, version control, documentation, and agile methodologies.
Strong experience in machine learning/AI research and technical support.
Deep understanding of modern machine learning architectures and optimization techniques.
Proficiency in ML frameworks like PyTorch, TensorFlow, Keras.
Extensive familiarity with Nvidia GPUs, software stacks (CUDA, NCCL), and HPC technologies.
Proficiency in big data frameworks (Spark, Hadoop).
Experience with data warehousing tools (Snowflake, SQL Server, Google BigQuery) is a plus.
Experience with container technologies (Docker, Singularity) and orchestration (Kubernetes).
Knowledge of project management and CI/CD tools (Asana, Jira, GitHub, GitLab, Jenkins).
Detail-oriented expertise, with strong problem-solving skills to support research.
Excellent communication skills, able to simplify complex tech concepts.
Strong team player with a service mindset, able to guide researchers.
Quick learner, stays updated on new technologies.
Strong project management and organizational skills.
Proven track record of success in working in a cross-functional team in an agile environment.
This is a full-time position based in MA, with a hybrid schedule (combination of in-person / remote). Harvard University supports a hybrid workplace model which will actively support some remote work. Specific days and schedules for on-site work and remote work will be discussed during the interview process. Please note hybrid workers must reside in a state where Harvard is registered to do business (CA, CT, GA, IL, MA, MD, ME, NH, NJ, NY, RI, VA, VT, and WA).
Work is performed in an office setting primarily in Allston, MA.
We are unable to provide visa sponsorships for these positions.
This position has a 180 day orientation and review period.
During the interview process, candidates will be notified of any additional exercises or presentations that may be required for this position.
The health of our workforce is a priority for Harvard University. With that in mind, we strongly encourage all employees to be up to date on CDC-recommended vaccines.
Harvard University is devoted to excellence in teaching, learning, and research, and to developing leaders in many disciplines who make a difference globally. The University, which is based in Cambridge and Boston, Massachusetts, has an enrollment of over 20,000 degree candidates, including undergraduate, graduate, and professional students. Harvard has more than 360,000 alumni around the world. The University has twelve degree-granting Schools in addition to the Radcliffe Institute for Advanced Study, offering a truly global education. Established in 1636, Harvard is the oldest institution of higher education in the United States.