Harvard University

Harvard University

Machine Learning and Generative AI Engineer, Digital Transformation

Boston, Massachusetts

No sponsorshipDetected 21 days ago
PythonCode ReviewNoSQLVector DatabasesAWSGCPAzureCI/CDLinuxKafkaMachine LearningDeep LearningTensorFlowPyTorchSparkAirflowNLPLLMsRAGLangGraphStatisticsA/B TestingResearchLeadership

About the role

  • It is among the world's most trusted sources of management education and thought leadership.
  • This key technical leadership role requires hands-on expertise across the full machine learning and AI lifecycle.
  • You will be highly influential in advancing our GenAI capabilities, guiding the teams towards impactful and ethical AI.

Responsibilities

  • Architect, build, maintain, and improve a suite of GenAI applications and their underlying systems.
  • Establish reusable frameworks to streamline model building, deployment and monitoring. Incorporate comprehensive logging, tracing, and alerting mechanisms.
  • Build guardrails, compliance rules, and oversight workflows into the GenAI application platform, including approval chains for model updates and staged rollouts for production releases.
  • Develop templates, guides, and sandbox environments to support onboarding of new contributors and experimentation with emerging techniques
  • Ensure user-facing applications built on the GenAI application platform are safe and reliable, enforcing rigorous validation and testing before publishing, and implement a clear peer review process.
  • Work closely with data scientists and analysts to develop and deploy new product features across web and mobile applications.
  • Partner with project managers to ensure projects are delivered on time and within budget.
  • Collaborate with Technical Product Managers to track algorithmic performance KPIs and prioritize performance improvements based on effort and impact.
  • You will collaborate with data scientists, product managers, and data engineers to operationalize AI models in production, drive core platform capabilities, and apply these in a variety of domains.
  • You will also develop and deploy novel approaches to optimize existing AI systems and maximize their business value.

Nice to have

  • Experience with embedding models and tuning vector databases (e.g., Qdrant, Pinecone, Weaviate) to improve semantic search and retrieval performance.
  • Experience with relational and NoSQL databases, big data tools (Spark, Kafka), Linux environments, and at least one major cloud provider (AWS, GCP, Azure).

Skills

  • Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline desired
  • Minimum of two to three years' software development experience with Python and SQL.
  • Minimum two to three years of experience using PyTorch or Tensorflow, including optimizing code for GPU clusters
  • Solid understanding of the theoretical foundations of LLMs, including Transformer architectures and self-attention mechanisms.
  • Familiarity with data pipeline and workflow management tools (e.g., Airflow, Prefect, or Step Functions).
  • Additional Information
  • Standard Hours/Schedule: 40 hours per week
  • Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
  • Pre-Employment Screening: Identity, Education, Criminal
  • Other Information:
  • A cover letter is required to be considered for this opportunity.
  • Work Format Details

Benefits

  • Our benefits include, but are not limited to:
  • 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
  • Professional development opportunities including tuition assistance and reimbursement
  • Commuter benefits, discounts and campus perks
  • Learn more about these and additional benefits on our Benefits & Wellbeing Page.
  • Automate machine learning pipelines, monitor performance and costs, and optimize models by using techniques such as LoRA/QLoRA and other parameter-efficient methods.
  • Apply an entrepreneurial mindset to identify opportunities to optimize business processes, improve user experiences, and prototype solutions that demonstrate value.
  • Mentor and educate team members to adopt best practices in writing and maintaining production-grade machine learning code.

Company info

  • We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives.

Equal opportunity

  • EEO/Non-Discrimination Commitment Statement
  • equal opportunity and non-discrimination.

Visa & Work Authorization

  • Harvard University is unable to provide visa sponsorship for this position
  • Certain visa types and funding sources may limit work location.

This listing is sourced directly from Harvard University's careers page and normalized into a canonical job model.