65718BRAuto req ID:65718BRJob Code:I1360P IT Data Architect Prof VI Department Office Location:USA - MA - Boston Business Title:Principal Machine Learning Engineer, Generative AI Products, Digital TransformationSub-Unit:------------ Salary Grade (https://hr.harvard.edu/salary-ranges#ranges) :060Time Status:Full-time Union:00 - Non Union, Exempt or Temporary Additional Qualifications and Skills:Other Required Qualifications:

• Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline or equivalent experience.

• Relevant work experience designing and implementing big data and machine learning solutions.

Additional/Desired Qualifications:

• Minimum of ten years’ software development experience with Python and SQL.

• Minimum of four years’ experience building pipelines to deploy NLP and deep learning models into production in a cloud environment

• Minimum four years’ experience using PyTorch, Tensorflow, or MXNet, along with optimizing code for GPU clusters

• Expert level experience building advanced workflows such as retrieval augmented generation, model chaining, dynamic prompting, PEFT/SFT, etc. using Langchain and similar tools

• 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

• Understand the underlying fundamentals such as Transformers, Self-Attention mechanisms that form the theoretical foundation of LLMs

• Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; and at least one cloud provider solution (AWS, GCP, Azure).

• Knowledge of data pipeline and workflow management tools.

• Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.

• Strong leadership and effective interpersonal skills, including good oral and written communication, with the ability to convey sophisticated concepts in an easy-to-understand way to a wide variety of audiences, both technical and non-technical.

• Strives to learn new skills, test the limits, and stretch capabilities maximizing opportunities to innovate and harness new ideas, emerging technologies and toolsets.

• Expert-level experience in designing, building and managing applications to process large amounts of data in a cloud ecosystem or other big data frameworks.

• Experience building systems to perform real-time data processing using scalable data streaming frameworks.

Please note candidates with less experience may be considered for a grade 59 salary band.Additional Information:This role is offered as a hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus a determined number of days per month. Specific days and schedule will be determined between you and your manager.

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.Department:Digital TransformationPre-Employment Screening:Criminal, Education, IdentityJob Function:Information Technology School/Unit:Harvard Business School 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.Basic Qualifications:

• Minimum of seven years’ post-secondary education or relevant work experience

Position Description:As a Principal Machine Learning Engineer on our GenAI applications team, you will help lead development of innovative generative AI products that address the needs of our constituents (students, alumni, faculty, researchers, staff, and community at large). This key technical leadership role requires leadership experience as well as hands-on expertise across the full machine learning lifecycle. In this role, you will lead machine learning engineers and collaborate with data scientists, product managers, and data engineers to operationalize machine learning models in production and manage the lifecycle of artificial intelligence algorithms on a variety of domains. You will develop and deploy novel approaches to optimize existing machine learning systems to maximize their business value.

You will also help us build and scale our GenAI application platform. This platform will be the hub within Harvard Business School (HBS) where GenAI application developers can share their data and code. As custodians of this platform, we intend to use the best practices in the field along with existing repositories to expedite the path from prototype for GenAI applications and unlock economies of scale. You will be highly influential in advancing our GenAI applications and guide teams towards impactful and ethical AI. We seek an expert who is eager to grow and disseminate GenAI model expertise across the organization. As a senior member of the technical staff, you will mentor others in emerging technologies and evangelize the use of best practices and cutting-edge tools across the team.

• Play an instrumental and influential role in driving Generative AI vision, strategy, and architecture.

• Architect, build, maintain, and improve new and existing suite of GenAI applications and their underlying systems.

• Automate machine learning pipelines, monitor performance and costs, and optimize models by using techniques such as LoRA/QLoRA.

• Establish reusable frameworks to streamline model building, deployment and monitoring. Incorporate comprehensive monitoring, logging, tracing, and alerting mechanisms.

• Build guardrails, compliance rules and oversight workflows into the GenAI application platform, such as establishing approval chains for model updates and staged rollout for production releases

• Develop templates, guides and sandbox environments for easy onboarding of new contributors and experimentation with new techniques

• Ensure development of user-facing applications in the GenAI application platform is easy and safe by enforcing rigorous validation testing before publishing user-generated models and implement a clear peer review process of applications

• Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value.

• Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps.

• Contribute to and promote good software engineering practices across the team.

• Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code.

• Actively contribute to and re-use community best practices.

• Monitor, debug, track, and resolve production issues.

• Work with project managers to ensure that projects proceed on time and on budget.

• Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs and prioritize performance improvements based on effort and impact.

• Mentor others in emerging data, machine learning and generative AI tools and technologies.

• Serve as a lead technical resource for Generative AI, Big Data/Machine Learning, partnering with internal HBS technical partners and stakeholders, and vendors in development efforts.

• Complete other responsibilities as assigned.

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.Benefits:We invite you to visit Harvard's Total Rewards website (https://hr.harvard.edu/totalrewards) to learn more about our outstanding benefits package, which may include:

• Paid Time Off: 3-4 weeks of accrued vacation time per year (3 weeks for support staff and 4 weeks for administrative/professional staff), 12 accrued sick days per year, 12.5 holidays plus a Winter Recess in December/January, 3 personal days per year (prorated based on date of hire), and up to 12 weeks of paid leave for new parents who are primary care givers.

• Health and Welfare: Comprehensive medical, dental, and vision benefits, disability and life insurance programs, along with voluntary benefits. Most coverage begins as of your start date.

• Work/Life and Wellness: Child and elder/adult care resources including on campus childcare centers, Employee Assistance Program, and wellness programs related to stress management, nutrition, meditation, and more.

• Retirement: University-funded retirement plan with contributions from 5% to 15% of eligible compensation, based on age and earnings with full vesting after 3 years of service.

• Tuition Assistance Program: Competitive program including $40 per class at the Harvard Extension School and reduced tuition through other participating Harvard graduate schools.

• Tuition Reimbursement: Program that provides 75% to 90% reimbursement up to $5,250 per calendar year for eligible courses taken at other accredited institutions.

• Professional Development: Programs and classes at little or no cost, including through the Harvard Center for Workplace Development and LinkedIn Learning.

• Commuting and Transportation: Various commuter options handled through the Parking Office, including discounted parking, half-priced public transportation passes and pre-tax transit passes, biking benefits, and more.

• Harvard Facilities Access, Discounts and Perks: Access to Harvard athletic and fitness facilities, libraries, campus events, credit union, and more, as well as discounts to various types of services (legal, financial, etc.) and cultural and leisure activities throughout metro-Boston.

Work Format:Hybrid (partially on-site, partially remote) LinkedIn Recruiter Tag (for internal use only):#LI-KR1About Us:Founded in 1908 as part of Harvard University, Harvard Business School (http://www.hbs.edu) (www.hbs.edu) is located on a 40-acre campus in Boston. The School offers two full-time MBA and PhD programs, more than 175 Executive Education programs, and certificates and courses through Harvard Business School Online. For more than a century, Harvard Business School faculty have drawn on their research, connection to practice, global expertise, and passion for teaching to educate leaders who make a difference in the world. The School and its curriculum attract the boldest thinkers and the most collaborative learners who will shape the practice of business and entrepreneurship around the globe.