Machine Learning Engineer III Position Available In Suffolk, Massachusetts

Machine Learning Engineer III

Location:

Boston, Massachusetts

Category:

Data Science & Machine Learning

Requisition ID:

249780
Job Description

Who We Are:

Wayfair is one of the world’s largest online destinations for home goods. To deliver an exceptional customer experience at scale, we rely heavily on machine learning and AI systems that power everything from delivery date prediction to multi-modal systems for visual diagnostics to agentic workflow automation.
As an ML Engineer within the Supply Chain and Retail Tech AI org, you’ll be at the forefront of transforming Wayfair Supply Chain and Support operations by developing robust, reliable and production-grade ML and AI systems. You will work closely with ML scientists to launch highly impactful and scalable ML models leveraging modern MLOps best practice and tools. You will drive significant business impact by designing and building complex Multi-modal and Agentic AI systems that are revolutionizing the way the industry operates.
Here are some of the key projects our team works on:

Vision-LLM:

Gen AI model for automating visual diagnostics and resolution for product refund
Customer Service Co-Pilot and Agentic workflow automation: Blog

Delivery Date Prediction:

Scalable Quantile Regression model that balances faster promise vs reliability: Blog

Personalization:

Uplift model for predicting the effectiveness of different customer service policy

What You’ll Do:

Build and own ML production systems for both real-time and batch inference, ensuring scalability, reliability, observability, and low latency.
Lead ML service integration with partner systems by establishing ownership boundaries, API contracts, clear SLAs, and fallback mechanisms
Architect and build complex multi-modal and Agentic AI systems by leveraging the latest advancement in LLM
Collaborate with ML Scientists to build reusable and scalable production-grade training code and pipelines using modern MLOps practices and infrastructure (GCP and open source)
We Are a

Match Because You Have:

Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related technical field or equivalent practical experience
5+ years of relevant industry experience, preferably including previous experience in ML infrastructure or AI/ML engineering
Strong programming skills in Python and experience with production-quality codebases
Experience with cloud platforms (preferably GCP), containerization (Docker), orchestration (Kubernetes), and CI/CD workflows. Familiarity with monitoring and observability tools (e.g., Datadog).
Able to work autonomously in cross-functional teams, communicate clearly with ML scientists and software engineers, and balance engineering quality with business impact. Comfortable leading technical discussions and driving alignment without formal authority.
Nice to

Have:

Proven experience deploying and integrating ML/AI models into production systems
Familiarity with MLOps and AIOps practices and tools (e.g. data pipeline, model orchestration, feature store)
Experience building RAG and agentic AI systems
Why You will Love Working With Us
Fun team outings like kayaking the Charles and Boda Borg,
Early adopters of new technology within Wayfair
Hackathons to explore new ideas

Time Off:

Paid Holidays
Paid Time Off (PTO)

Health & Wellness:

Full Health Benefits (Medical, Dental, Vision, HSA/FSA)
Life Insurance
Disability Protection (Short Term & Long Term Disability)

Global Wellbeing:

Gym/Fitness discounts (including US Peloton, Global ClassPass, and various regional gym memberships)
Mental Health Support (Global Mental Health, Global Wayhealthy Recordings)
Caregiver Services

Financial Growth & Security:

401K Matching (Employee Matching Program)
Tuition Reimbursement Financial Health Education (Knowledge of Financial Education – KOFE)
Tax Advantaged Accounts

Family Support:

Family Planning Support
Parental Leave
Global Surrogacy & Adoption Policy

Professional Development & Recognition:

Rewards & Recognition Global Employee Anniversary Awards Paid Volunteer Work Unique Perks:

Employee Discount U.S. Bluebikes Membership
Global Pod Outings

Work/Life Balance:

Emphasizing a supportive & flexible work environment that encourages a balance between personal and professional commitments
Candidates for this position are to be based, or plan to relocate to Boston, and will be expected to comply with their team’s hybrid work schedule requirements. Our teams are onsite in our Boston office Tuesday-Thursday, and remote Monday and Friday.

Massachusetts Applicants:

I understand that it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
About Wayfair Inc.
Wayfair is one of the world’s largest online destinations for the home. Whether you work in our global headquarters in Boston, or in our warehouses or offices throughout the world, we’re reinventing the way people shop for their homes. Through our commitment to industry-leading technology and creative problem-solving, we are confident that Wayfair will be home to the most rewarding work of your career. If you’re looking for rapid growth, constant learning, and dynamic challenges, then you’ll find that amazing career opportunities are knocking.
No matter who you are, Wayfair is a place you can call home. We’re a community of innovators, risk-takers, and trailblazers who celebrate our differences, and know that our unique perspectives make us stronger, smarter, and well-positioned for success. We value and rely on the collective voices of our employees, customers, community, and suppliers to help guide us as we build a better Wayfair – and world – for all. Every voice, every perspective matters. That’s why we’re proud to be an equal opportunity employer. We do not discriminate on the basis of race, color, ethnicity, ancestry, religion, sex, national origin, sexual orientation, age, citizenship status, marital status, disability, gender identity, gender expression, veteran status, genetic information, or any other legally protected characteristic.