Senior AI/ML Systems Engineer – Research & HPC (Hybrid)
Harvard University
Cambridge (MA)
Hybrid
USD 140,000 - 190,000
Full time
14 days+
Application generator
An application made for this job — a tailored resume and cover letter that speak straight to the posting.
Get past ATS filters
Benefits offered by this job
Generous paid time off including parental leave
Medical, dental, and vision coverage from day one
Retirement plans with university contributions
Professional development opportunities
Job summary
An esteemed educational institution in Cambridge, MA, is seeking a Senior Research Software Engineer to develop and implement advanced ML and AI systems. The role involves collaboration with researchers on innovative projects, optimizing performance in AWS and HPC environments, and supporting high-quality software delivery. Ideal candidates will have strong programming skills in Python and C/C++, and experience with machine learning frameworks. This position offers a hybrid work model and a benefits-eligible, two-year term appointment.
Qualifications
Strong programming skills in Python/C/C++.
Experience with ML frameworks like PyTorch and TensorFlow.
Seven years post-secondary education or relevant work experience.
Responsibilities
Design, build, maintain ML/AI systems and research software.
Develop and optimize ML training/inference pipelines.
Collaborate closely with faculty and researchers on systems engineering.
Skills
Python
C/C++
Machine Learning
AWS
Collaboration
Education
BS or MS in Computer Science, Computer Engineering, Data Science, or related field
Tools
PyTorch
TensorFlow
AWS Cloud
Job description
An esteemed educational institution in Cambridge, MA, is seeking a Senior Research Software Engineer to develop and implement advanced ML and AI systems. The role involves collaboration with researchers on innovative projects, optimizing performance in AWS and HPC environments, and supporting high-quality software delivery. Ideal candidates will have strong programming skills in Python and C/C++, and experience with machine learning frameworks. This position offers a hybrid work model and a benefits-eligible, two-year term appointment.