Machine Learning and Generative AI Engineer, Digital Transformation
Harvard University2 months ago
Boston, MA, USAMid Level
Responsibilities
- Architect, build, maintain, and improve GenAI applications and their underlying systems.
- Automate ML pipelines, monitor performance and costs, and optimize models using LoRA, QLoRA, and other parameter-efficient methods.
- Establish reusable frameworks for model building, deployment, monitoring, logging, tracing, and alerting.
- Build platform guardrails, compliance rules, approval workflows, and staged production rollouts.
- Develop templates, guides, and sandbox environments for onboarding and experimentation.
- Ensure user-facing GenAI applications are safe and reliable through validation, testing, and peer review.
- Collaborate with data scientists and analysts to deploy product features across web and mobile applications.
- Mentor team members in production-grade machine learning software practices and contribute to open-source and community best practices.
- Monitor, debug, and resolve production issues.
- Partner with project managers and technical product managers on delivery, KPIs, and performance priorities.
Requirements
- At least two years of software development experience with Python and SQL.
- At least two years of experience building and deploying NLP and deep-learning model pipelines in a cloud environment.
- At least two years of experience with PyTorch or TensorFlow, including GPU-cluster code optimization.
- Experience building RAG, model chaining, dynamic prompting, and parameter-efficient fine-tuning workflows with LangChain, LangGraph, or similar frameworks.
- Experience establishing model guardrails and developing bias detection and mitigation techniques.
- Experience with embedding models and vector databases such as Qdrant, Pinecone, or Weaviate.
- Understanding of LLM foundations, including Transformer architectures and self-attention mechanisms.
- Experience with relational and NoSQL databases, Spark, Kafka, Linux, and at least one major cloud provider.
- Familiarity with Airflow, Prefect, or Step Functions for data pipeline and workflow management.
- Strong software engineering fundamentals, including unit testing, code reviews, and design documentation.
- A bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline is desired.
- Minimum of five years of post-secondary education or relevant work experience.
Benefits
- Hybrid work arrangement based at the Boston campus, with staff expected onsite at least three days per week and onsite coverage Monday through Friday.
- Standard schedule of 40 hours per week.
- Generous paid time off, including parental leave.
- Medical, dental, and vision insurance beginning on day one.
- Retirement plans with university contributions.
- Wellbeing and mental health resources.
- Family and caregiver support, professional development, tuition assistance, commuter benefits, discounts, and campus perks.