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Senior Machine Learning Engineer, Generative AI Products, HBS Foundry at HarvardUniversity
HarvardUniversityBoston, MA, us·1d ago
SeniorFull-timeRustRailsMachine Learning
Salary Range
$132,600 - $179,400 /year
This salary is estimated based on similar roles. The actual salary may vary.
About the Role
We are looking for a Lead Web Developer to join our team and work on highly complex projects. This role involves comprehensive application and web development, focusing on implementing complex business solutions and developing strategic coding approaches.
Key Responsibilities
- →Architect, build, maintain, and improve new and existing suite of GenAI applications and their underlying systems
- →Automate machine learning pipelines, monitor performance and costs, and optimize models using techniques such as LoRA/QLoRA
- →Establish reusable frameworks to streamline model building, deployment, and monitoring
- →Build guardrails, compliance rules, and oversight workflows into the GenAI application platform
- →Develop templates, guides, and sandbox environments for easy onboarding of new contributors
- →Ensure development of user-facing applications is easy and safe by enforcing rigorous validation testing
- →Use entrepreneurial spirit to identify new opportunities to optimize business processes
- →Work closely with data scientists and analysts to create and deploy new product features
- →Contribute to and promote good software engineering practices across the team
- →Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code
- →Actively contribute to and re-use community best practices
- →Monitor, debug, track, and resolve production issues
- →Work with project managers to ensure that projects proceed on time and on budget
- →Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs
Requirements
- ✓Experience with GenAI applications and machine learning pipelines
- ✓Knowledge of techniques such as LoRA/QLoRA for model optimization
- ✓Ability to establish reusable frameworks for model building, deployment, and monitoring
- ✓Understanding of compliance rules and oversight workflows
- ✓Experience with validation testing and peer review processes
- ✓Strong software engineering practices and mentorship skills
- ✓Ability to work with data scientists and analysts to deploy new product features
- ✓Experience with monitoring, debugging, and resolving production issues
- ✓Project management collaboration skills
- ✓Performance tracking and improvement prioritization skills
