Apply on Employer Site

Harvard Business School · 3 hours ago

Senior Machine Learning Engineer, Generative AI Products, HBS Foundry

Boston, MA

Full-time

Hybrid

Senior Level

5+ years exp

Harvard Business School is a prestigious institution dedicated to fostering innovation and collaboration. They are seeking a Senior Machine Learning Engineer to lead the development of complex AI-driven applications, focusing on enhancing user experiences and optimizing machine learning processes.

AlumniEducationHigher EducationUniversities

Growth Opportunities

No H1B

Responsibilities

Build trust and collaboration by being present on-site and engaging directly with colleagues and various constituents

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

Complete other responsibilities as assigned

Qualification

PythonNLPDeep LearningCloud EnvironmentSQLPyTorchTensorFlowModel OptimizationData Pipeline ManagementSoftware Engineering PracticesCollaborationMentoringProblem Solving

Required

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

Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired

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

Benefits

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

Company

Harvard Business School

Glassdoor4.4

Harvard Business School is an educational institution that offers two-year residential programs leading to an MBA, Ph.D., or DBA degree. It is a sub-organization of Harvard University.

Founded in 1908

Boston, Massachusetts, USA

1001-5000 employees