Position Description
We are seeking a talented Generative AI Engineer to join our team. In this role, you will design, develop, and deploy state-of-the-art generative AI models, directly impacting our platform's ability to provide interactive and intelligent tools for our users.
As a Senior Data Scientist specializing in Generative AI applications, you will play a pivotal role in developing innovative generative AI products that support the Harvard Business School (HBS) Foundry team and learners on our platform. This key technical role requires hands-on expertise across data science, machine learning, and AI solutions. You will manage the lifecycle of artificial intelligence algorithms and tools across a variety of domains. The Foundry Team will support with domain knowledge.
AI Tool Development and Implementation Design and implement efficient data pipelines for data collection, cleaning, labeling, and preprocessing Ensure quality of datasets tailored for LLM training for each product. Build data science pipelines from feature generation, data visualization and models evaluation; design the solution, build code and provide documentation with ways of working to maximize time to value, re-usability, and scalability. Designing, developing, deploying, and implementing multi-agent AI tools that: Assess and provide feedback on venture-related submissions Automatically generate pitch decks, financial projections, marketing strategies, and other materials to support entrepreneurs Act as a counterparty to simulate important entrepreneurial interactions such as customer interviews, negotiations with an investor, etc. Designing generative AI models using techniques like natural language processing and machine learning that can power interactive tools on HBS Foundry. Designing an AI-powered system that collects key factors to determine a learner's profile, entrepreneurial progress, and venture progress, and provides customized learning pathways based on these factors. Integrating AI tools into the HBS Foundry platform in a seamless manner so they are easy for users to access and utilize. Collaborate on technical vision to accelerate product impact through cutting-edge LLM innovations. Building guardrails, compliance rules, and oversight workflows into the GenAI tools and Foundry platform. Continually improving AI tools using feedback from users to ensure they are providing valuable assistance. Project and Performance Management Monitor, debug, track, and resolve production issues. Work with the Foundry Project Director to ensure that projects proceed on time and on budget. Collaborate with Product Managers to ensure proper tracking of performance KPIs and prioritize improvements based on effort and impact. Presenting prototypes and progress updates to stakeholders. Research and Collaboration Staying up to date on the latest advances in AI/ML research and identifying how new techniques could enhance the HBS Foundry platform. Collaborating with a team of engineers, designers, and subject matter experts to deliver high-quality, helpful AI-powered experiences. This role is responsible for other duties as assigned. Basic Qualifications Minimum of seven years' post-secondary education or relevant work experience 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. Benefits
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