Senior Machine Learning Engineer, Generative AI Applications

University of Illinois - Cambridge, MA

Full-time - Senior

Hybrid - Cambridge, MA

Educational Services

About the position

The Senior Machine Learning Engineer for Generative AI Applications at Harvard Business School will play a pivotal role in the Digital Transformation team, focusing on deploying innovative digital and emerging technology solutions in education. This position involves collaborating with various stakeholders to operationalize machine learning models, optimize existing systems, and enhance business value through advanced algorithms and automated processes.

Responsibilities

• Architect, build, maintain, and improve new and existing suite of algorithms and their underlying systems.
• Automate machine learning pipelines and monitor and optimize machine learning solutions.
• Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance tuning, and A/B testing.
• 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.
• Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation.
• Write efficient and well-organized software to ship products in an iterative, continual-release environment.
• 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.
• 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.

Requirements

• Minimum of seven years' post-secondary education or relevant work experience.
• Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.
• Minimum of five years' software development experience with Python and SQL.
• Minimum of three years' experience in developing and deploying machine learning systems into production in a cloud environment.
• Minimum of two years' experience testing, maintaining, or launching software products and minimum of one year of experience with software design and architecture.
• 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.

Nice-to-haves

• Experience with neural networks, deep learning, and reinforcement learning, using frameworks such as TensorFlow.
• Experience with Natural Language Processing (NLP), Large Language Models (LLMs), and/or Recommendation Engines.
• Relevant working experience with Docker and Kubernetes.

Benefits

• Paid Time Off: 3-4 weeks of accrued vacation time per year, 12 accrued sick days per year, 12.5 holidays plus a Winter Recess, 3 personal days per year, and up to 12 weeks of paid leave for new parents who are primary caregivers.
• Comprehensive medical, dental, and vision benefits, disability and life insurance programs, along with voluntary benefits.
• Child and elder/adult care resources including on-campus childcare centers, Employee Assistance Program, and wellness programs.
• 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 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.
• Programs and classes for professional development at little or no cost, including through the Harvard Center for Workplace Development and LinkedIn Learning.
• Various commuter options including discounted parking, half-priced public transportation passes, and biking benefits.