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