Machine Learning Engineer, Digital Transformation

19-May-2023

Harvard Business School

62609BR

Position Description

Be a pioneer in business, education, and global impact by joining the Harvard Business School Digital Transformation team - a “startup with assets,” where you will have the chance to deploy cutting-edge digital- and emerging-technology education solutions. Where else can you make a difference at the intersection of cutting-edge technology, world-class education, noble purpose, and timeless legacy?

As a Machine Learning Engineer, you will collaborate with Data Scientists, Product Managers, and Data Engineers to operationalize the Machine Learning Models in production and manage the lifecycle of artificial intelligence algorithms on a broad set of domains. You will develop and deploy novel approaches to optimize existing machine learning systems to maximize their ongoing value.

Duties and Responsibilities include:

• Frame machine learning problems
• 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 testing and A/B testing
• Use your entrepreneurial spirit to identify new opportunities to optimize business processes and 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
• Communicate clearly and effectively to technical and non-technical audiences equally well
• Actively contribute to and re-use community best practices
• Monitoring and adapting content influx and datasets to prevent algorithm corruption
• Monitor input and output signals to ensure progress toward designated goals
• Work with product managers to ensure that projects proceed on time and on budget
• Work with other engineers to develop a working understanding of how algorithms are developing
• Document process steps to ensure reasonable human oversight
• Work with other engineers to monitor changes in development and implement symbiotic learning engagements between iterative machine learning models
• Perform other duties as necessary and/or assigned

Basic Qualifications

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

Additional Qualifications and Skills

Additional Required Qualifications:

• Bachelors or advanced degree in engineering, computer science, mathematics, or a related field and/or an equivalent 6+ years relevant work experience
• 3+ years experience developing and deploying machine learning systems into production

• Proficiency in PyTorch, Python, Java, C++, Scala, or OpenAI is a plus
• Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; SaaS companies; and at least one cloud provider solution (AWS, GCP, Azure)
• Relevant working experience with Docker and Kubernetes is a big plus
• Knowledge of data pipeline and workflow management tools
• Comfort controlling the big data feed that will be used to train AI algorithms
• Expertise in standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation
• 2 or more years of experience as a certified engineer
• Clear communication with data scientists, product managers and other engineers on project timelines, delays, advancements, and progression
• Hands-on knowledge of AI and ML best practices for: model building; automation; neural network enrichment;  iterative learning; “black box” problem-solving
• Strong time management skills
• Dedication to high-quality work output
• Understanding of engineering ethics, robotics ethics, AI creation ethics
• Comfort working in a small, remote team-based environment

Additional Information

This role is offered as remote possible or hybrid (some combination of onsite and remote) where you are required to be onsite at our Boston, MA based campus. 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 .

Benefits

We invite you to visit Harvard’s Total Rewards website 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.

Job Function

Information Technology

Department Office Location

USA - MA - Boston

Job Code

I0759P Applications Professional V

Work Format

Hybrid (partially on-site, partially remote)

Department

Digital Transformation (DTx)

Union

00 - Non Union, Exempt or Temporary

Pre-Employment Screening

Criminal, Education, Identity

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.

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.