Job summary
Job post source
This job is directly from Harvard University
Job overview
The Senior ML Research Engineer at Harvard University plays a key role in advancing AI/ML research by developing robust machine learning codebases and supporting complex AI applications within the Kempner Institute.
Responsibilities and impact
The role involves advising researchers on software and data analysis design, building and maintaining software and data pipelines, collaborating with teams, providing project updates, and teaching sustainable software practices to ensure reproducible research.
Compensation and benefits
The position offers a salary at grade level 060 with comprehensive benefits including paid time off, medical/dental/vision insurance from day one, retirement plans, mental health resources, family support, professional development, and commuter perks.
Experience and skills
Candidates must have at least seven years of relevant experience or education, expertise in software engineering best practices, strong machine learning/AI research experience, proficiency in PyTorch, knowledge of Nvidia GPU and HPC technologies, excellent communication, and teamwork skills.
Career development
The job offers professional development opportunities including tuition assistance and reimbursement to support career growth.
Work environment and culture
Harvard University fosters a diverse, inclusive, and collaborative environment dedicated to innovation and research excellence, supporting a healthy work-life balance.
Company information
Harvard University is a prestigious institution with a large central administration supporting its schools and communities, known for its commitment to diversity, innovation, and academic excellence.
Team overview
The candidate will join the Kempner Institute's Research & Engineering team, a dynamic group focused on AI research supported by one of the largest academic AI supercomputers.
Job location and travel
The position is based on a Harvard campus with some remote work options within specified states, requiring work location sponsorship compliance.
Unique job features
The role involves working with one of the world's largest academic AI supercomputers and contributing to cutting-edge AI research in a collaborative academic setting.
Company overview
Harvard University, founded in 1636, is a prestigious Ivy League institution located in Cambridge, Massachusetts. It offers a wide range of undergraduate, graduate, and professional programs across various disciplines, including arts, sciences, business, law, and medicine. The university generates revenue through tuition fees, research grants, endowments, and donations. Harvard's notable history includes producing numerous U.S. presidents, Nobel laureates, and influential leaders, making it a globally recognized center for academic excellence and innovation.
How to land this job
Position your resume to highlight your technical leadership in machine learning and AI research engineering, emphasizing experience with PyTorch, Nvidia GPU stack, and HPC technologies to align with Harvard's advanced AI supercomputing environment.
Emphasize your skills in software engineering best practices such as code reviews, version control, documentation, and agile methodologies, as well as your ability to collaborate cross-functionally and communicate complex technical concepts clearly.
Apply through multiple channels including Harvard University's official careers page and LinkedIn to maximize your application visibility and ensure it reaches the right hiring managers.
Connect on LinkedIn with current engineers and researchers at Harvard's Kempner Institute or Central Administration, using ice breakers like expressing admiration for their AI supercomputing projects or asking about recent research collaborations to initiate meaningful conversations.
Optimize your resume for ATS by incorporating keywords from the job description such as 'machine learning architectures,' 'software engineering best practices,' 'reproducible research,' 'PyTorch,' and 'HPC technologies' to pass automated screenings effectively.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications, identify multiple application portals, and find relevant Harvard University contacts on LinkedIn, allowing you to focus your energy on preparing for interviews and networking.
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