Harvard University is hiring a Senior Machine Learning Engineer

Harvard University seeks a Senior Machine Learning Engineer to lead comprehensive development for highly complex projects, typically as part of a team implementing complex business solutions. You will deliver strategic and expert coding, focusing on the overarching development strategy for a large, complex, multi-faceted application within a vibrant community dedicated to Harvard's world-changing mission.

What You'll Do

• 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 by using techniques such as LoRA/QLoRA.
• Establish reusable frameworks to streamline model building, deployment and monitoring. Incorporate comprehensive monitoring, logging, tracing, and alerting mechanisms.
• Build guardrails, compliance rules and oversight workflows into the GenAI application platform, such as establishing approval chains for model updates and staged rollout for production releases.
• Develop templates, guides and sandbox environments for easy onboarding of new contributors and experimentation with new techniques.
• Ensure development of user-facing applications in the GenAI application platform is easy and safe by enforcing rigorous validation testing before publishing user-generated models and implement a clear peer review process of applications.
• Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value.
• Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps.
• 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 and prioritize performance improvements based on effort and impact.

What We're Looking For

• Minimum of seven years’ post-secondary education or relevant work experience

Nice to Have

• Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline
• Minimum of five years’ software development experience with Python and SQL.
• Minimum of three years’ experience building pipelines to deploy NLP and deep learning models into production in a cloud environment
• Minimum three years’ experience using PyTorch, Tensorflow, or MXNet, along with optimizing code for GPU clusters
• Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools
• Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications using tools such as NeMo
• Experience with various embedding models and setting up and tuning vector databases to improve performance of semantic search and retrieval systems
• Understand the underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs
• Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; and at least one cloud provider solution (AWS, GCP, Azure).
• Knowledge of data pipeline and workflow management tools.
• Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.

Technical Stack

• Python, SQL, PyTorch, Tensorflow, MXNet, Langchain, NeMo, Hadoop, Spark, Kafka, Linux, AWS, GCP, Azure

Team & Environment

Part of a small, collaborative team within HBS Foundry. The environment combines the energy of a startup with the mission and reach of Harvard, and is passionate about innovation, learning, and impact. It's an exciting, fast-moving environment where new ideas matter and every team member has the opportunity to shape what comes next.

Benefits & Compensation

• Generous paid time off including parental leave
• Medical, dental, and vision health insurance coverage starting on day one
• Retirement plans with university contributions
• Wellbeing and mental health resources
• Support for families and caregivers
• Professional development opportunities including tuition assistance and reimbursement
• Commuter benefits, discounts and campus perks

Work Mode

This is a hybrid position based in Boston, MA.

Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives.