- Deep expertise in GPU hardware, architecture, and performance optimization.
- Mastery of Nvidia GPUs, software stacks (CUDA, cuDNN, TensorRT, NCCL), and HPC technologies.
- Advanced proficiency in GPU profiling and debugging tools such as Nsight and nvprof.
- In-depth knowledge of memory hierarchies, parallel programming, and optimization techniques relevant to GPUs.
- Solid experience in optimizing and scaling deep learning applications in production environments, especially on GPUs.
- Proficiency in deep learning frameworks like PyTorch, TensorFlow, Keras, optimized for GPU execution.
- Ability to transform research ideas into practical software implementations optimized for GPUs.
- Comprehensive understanding and hands-on experience with deep learning algorithms and applications.
- Proficiency in big data frameworks (Spark, Hadoop) emphasizing GPU acceleration.
- Skilled in container technologies (Docker, Singularity) and orchestration (Kubernetes) optimized for GPU workflows.
- Proficiency in implementing software engineering best practices such as code reviews, version control, documentation, and agile methodologies.
- Knowledge of project management and CI/CD tools (Asana, Jira, GitHub, GitLab, Jenkins).
- Experience with data warehousing tools (Snowflake, SQL Server, Google BigQuery) is a plus.
- Strong communication skills, capable of simplifying complex tech concepts.
- Excellent team player with a service mindset, able to guide researchers on GPU-related queries.
- Detail-oriented, with strong problem-solving skills to support GPU optimizations and troubleshooting.
- Quick learner, consistently updated on the latest GPU and HPC technologies.
- Strong project management and organizational skills.
- Demonstrated success in collaborating within 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.
- 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
- Paid Time Off: 3-4 weeks of accrued vacation time per year (3 weeks for support staff and 4 weeks for administrative/professional staff), 12 accrued sick days per year, 12.5 holidays plus a Winter Recess in December/January, 3 personal days per year (prorated based on date of hire), and up to 12 weeks of paid leave for new parents who are primary care givers.
- Health and Welfare: Comprehensive medical, dental, and vision benefits, disability and life insurance programs, along with voluntary benefits. Most coverage begins as of your start date.
- Work/Life and Wellness: Child and elder/adult care resources including on campus childcare centers, Employee Assistance Program, and wellness programs related to stress management, nutrition, meditation, and more.
- Retirement: University-funded retirement plan with contributions from 5% to 15% of eligible compensation, based on age and earnings with full vesting after 3 years of service.
- Tuition Assistance Program: Competitive program including $40 per class at the Harvard Extension School and reduced tuition through other participating Harvard graduate schools.
- Tuition Reimbursement: Program that provides 75% to 90% reimbursement up to $5,250 per calendar year for eligible courses taken at other accredited institutions.
- Professional Development: Programs and classes at little or no cost, including through the Harvard Center for Workplace Development and LinkedIn Learning.
- Commuting and Transportation: Various commuter options handled through the Parking Office, including discounted parking, half-priced public transportation passes and pre-tax transit passes, biking benefits, and more.
- Harvard Facilities Access, Discounts and Perks: Access to Harvard athletic and fitness facilities, libraries, campus events, credit union, and more, as well as discounts to various types of services (legal, financial, etc.) and cultural and leisure activities throughout metro-Boston.
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Senior AI/ML GPU Computing Engineer - Allston, United States - Harvard University
Description
Basic QualificationsMinimum of seven years' post-secondary education or relevant work experience (can be a combination of education and work experience).
Additional Qualifications and Skills
Position Description
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.
Core Duties
We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.
Job Summary
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 GPU-optimized computing infrastructures in the world. Additionally, the institute is hiring senior engineers with deep experience in optimizing algorithms and workloads for GPUs to facilitate cutting-edge research.
We are hiring a Senior AI/ML GPU Computing Engineer with a proven record of technical leadership and solid engineering skills to enhance our engineering team at the Kempner Institute. The Senior AI/ML GPU Computing Engineer will play a critical role in assisting researchers by optimizing their deep learning and AI algorithms for GPUs, implementing software engineering best practices, and managing GPU resources. They will also be responsible for disseminating code on open science platforms as open-source software, building distributed GPU computing infrastructure, and supporting research with high-performance GPU solutions. The selected candidate will utilize their expertise to tackle complex challenges in scalable GPU computing environments and provide 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 scalable GPU computing solutions for AI/ML 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.
Commitment to Equity, Diversity, Inclusion, and Belonging
Harvard University views equity, diversity, inclusion, and belonging as the pathway to achieving inclusive excellence and fostering a campus culture where everyone can thrive. We strive to create a community that draws upon the widest possible pool of talent to unify excellence and diversity while fully embracing individuals from varied backgrounds, cultures, races, identities, life experiences, perspectives, beliefs, and values.
Benefits
We invite you to visit Harvard's Total Rewards website ) to learn more about our outstanding benefits package, which may include:
This is a hybrid position that is based in Allston, Massachusetts. Additional details will be discussed during the interview process. All remote work must be performed within one of the Harvard Registered Payroll States, which currently includes Massachusetts, Connecticut, Maine, New Hampshire, Rhode Island, Vermont, Georgia, Illinois, Maryland, New Jersey, New York, Virginia, Washington, and California (CA for exempt positions only). Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements prior to employment.
