Harvard University

Harvard University

Machine Learning and Generative AI Engineer, Digital Transformation

Boston, Massachusetts

No sponsorshipDetected 68 days ago
PythonCode ReviewNoSQLVector DatabasesAWSGCPAzureCI/CDLinuxKafkaMachine LearningDeep LearningTensorFlowPyTorchSparkAirflowNLPLLMsRAGLangGraphStatisticsA/B TestingResearchLeadership

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odds of building a lasting career here

88Lottery-free
Cap-exempt (no lottery)100
Sponsors year-round100
Entry-level history60
PERM / green-card track50
Fits your clock70

Files H-1B any time — no cap, no lottery. The 2026 weighted-selection rule doesn't touch it, which makes this the strongest structural path for entry-level talent. Pay is often lower, but your odds of staying are dramatically higher.

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Employer immigration record

from this employer's Department of Labor filings

States it is exempt from the H-1B cap

In 9 Department of Labor filings, this employer states it is an institution of higher education — one of the statutory grounds for exemption from the H-1B cap. Cap-exempt employers can file year-round without entering the lottery.Employer's own attestation on a Department of Labor wage determination, not a USCIS determination — exemption is decided per petition.

Files H-1B transfers

11 transfer filings in the last year, covering 11 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Be a pioneer in business, education, and global impact by joining the Harvard Business School Digital Transformation team - a "startup with assets," where you will have the chance to deploy cutting-edge digital and emerging-technology education solutions.
  • This key technical leadership role requires hands-on expertise across the full machine learning and AI lifecycle.
  • As custodians of this platform, we will apply best practices and leverage existing repositories to accelerate the path from prototype for GenAI applications and unlock economies of scale.

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.
  • Support for families and caregivers

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).
  • We may conduct candidate interviews virtually (phone and/or via Zoom) and/or in-person for this role.
  • A cover letter is required to be considered for this opportunity.

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

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 are dedicated to creating a diverse and welcoming environment where everyone can thrive.
  • Harvard Business School (HBS), located on a 40-acre campus in Boston, was founded in 1908 as part of Harvard University.
  • 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

  • Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position
  • Certain visa types and funding sources may limit work location.
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This listing is sourced directly from Harvard University's careers page and normalized into a canonical job model.