Harvard University

Additional Qualifications and Skills

Other Required Qualifications:

• Advanced degree in computer science, data science, engineering, or a related field within AI/ML

Additional/Desired Qualifications:

• 3+ years of experience building (Generative) AI models and tools highly preferrable
• Experience working in a similar role in a startup environment preferrable
• Expertise in NLP, deep learning, and other relevant techniques
• Strong programming skills in Python and frameworks like TensorFlow
• Experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools
• Experience integrating AI into consumer-facing applications (front-end and back-end development for integrating AI solutions into web applications
• 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
• Experience working with a variety of relational SQL and NoSQL databases, big data tools (such as Hadoop, Spark, Kafka), and at least one cloud provider solution (AWS highly preferrable)
• Experience in using version control systems such as Git.
• Experience with containerization and orchestration tools like Docker and Kubernetes.
• Experience with API development and integration for AI services.
• Understanding of and experience with of software engineering best practices like version control, CI/CD, and containerization
• Experience establishing model guardrails and developing bias detection and mitigation techniques for AI applications
• Proficiency with various prompting techniques, with a clear understanding of tradeoffs between prompting and finetuning
• Experience with finetuning embedding models and tuning vector databases to improve performance of semantic search and retrieval systems
• Experience operationalizing end-to-end machine learning applications.
• Excellent communication and collaboration skills
• Passion for using AI to solve real-world problems

,

Additional Information

This role has the possibility of being remote or hybrid. We consider hybrid to be a combination of remote and onsite work at our Boston, MA based campus. HBS expects all staff to be onsite 3 days per week and departments provide onsite coverage Monday – Friday. Remote work may be considered for individuals living at least 100-mile radius from campus and where all work will be completed within a state that Harvard is registered to do business in (CA - exempt roles only, CT, GA, IL, MA, MD, ME, NH, NJ, NY, RI, VA, VT or WA). Specific hours and days onsite will be determined by business needs and are subject to change with appropriate advanced notice.

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.

Harvard Business School will not offer visa sponsorship for this opportunity.

Culture of Inclusion: The work and well-being of HBS is profoundly strengthened by the diversity of our network and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. Explore more about HBS work culture here https://www.hbs.edu/employment.,

EEO Statement

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability status, protected veteran status, gender identity, sexual orientation, pregnancy and pregnancy-related conditions, or any other characteristic protected by law.,

Commitment to Equity, Diversity, Inclusion, and Belonging

Harvard University views equity, diversity, inclusion, and belonging as the pathway to achieving inclusive excellence and fostering a campus culture where everyone can thrive. We strive to create a community that draws upon the widest possible pool of talent to unify excellence and diversity while fully embracing individuals from varied backgrounds, cultures, races, identities, life experiences, perspectives, beliefs, and values.