Machine Learning Scientist II

Who We Are

We are seeking a highly analytical, action-oriented AI Scientist to design and deploy innovative AI solutions for Wayfair's Customer Service team. In this role, you will apply large language models (LLMs) and LLMops expertise to transform complex customer service challenges into scalable, AI-driven tools that boost agent efficiency and elevate customer satisfaction. Success in this role requires comprehensive experience and deep expertise in Generative AI and Natural Language Processing, strong problem-solving skills, and the ability to work effectively across cross-functional teams. The ideal candidate is proficient in both qualitative and quantitative analysis and excels at communicating insights to drive meaningful business outcomes.

What You’ll Do

• Research and experiment with state-of-the-art generative AI techniques and algorithms, evaluating their performance on benchmark datasets and real-world scenarios.
• Conduct exploratory data analysis to uncover data patterns, relationships, and key features for model training.
• Develop and deploy machine learning models in production by collaborating with software engineers and using robust CI/CD practices; ensure these models are scalable, secure, and continuously monitored for performance with effective troubleshooting.
• Contribute to architectural and code review discussions to enhance our engineering ecosystem.
• Develop, fine-tune, and implement GenAI models to improve customer service interactions, such as smart chatbots and agentic AI tools, ensuring they align with Wayfair's data and context.
• Apply advanced prompt engineering and domain-specific fine-tuning to boost AI model response relevance and performance in customer service scenarios, using experiments to benchmark improvements.
• Collaborate with product managers, customer service operations, data engineers, and other stakeholders to translate business needs into technical solutions that integrate smoothly into agent workflows.
• Develop key success metrics and build evaluation frameworks to regularly assess model output quality, using data-driven insights to continuously enhance AI capabilities.
• Stay current with the latest research in GenAI, transformer architectures, and agentic AI, proactively experimenting with new techniques and tools to champion ideas that enhance Wayfair's customer service experience.

What You’ll Need

• PhD with 0-1+ years of experience or Master’s in Computer Science, Data Science, Machine Learning, or a related quantitative field with 2+ years of full-time industry experience in applied research.
• Deep understanding of data engineering concepts with experience in building scalable data pipelines for collecting, processing, and transforming data.
• Proven track record of delivering successful machine learning projects from conception to production, demonstrating strong deployment, problem-solving, and maintenance skills.
• Professional coding expertise in languages like Python and R, proficiency in SQL, and experience with data visualization tools; skilled in using ML frameworks (TensorFlow, PyTorch) and implementing CI/CD, containerization, and version control best practices.
• Hands-on experience with large language models (e.g., GPT, BERT, Transformers) and Retrieval-Augmented Generation (RAG) techniques, and fine-tuning LLM models to address specific business challenges.
• Solid understanding of natural language processing methods and traditional machine learning techniques to effectively tackle diverse problems.
• Excellent communication skills, with the ability to clearly articulate complex AI concepts to non-technical stakeholders while collaborating across teams.
• Demonstrated ability to quickly learn new tools and techniques in a fast-paced, evolving environment, while managing multiple priorities with a high level of attention to detail and staying current with the latest ML research.

Assets

• Experience with agentic AI systems and LLMOps principles for model lifecycle management, performance evaluation, and automated testing.
• A PhD in AI or a strong publication record in top conferences and journals

Assistance For Individuals With Disabilities

Wayfair is fully committed to providing equal opportunities for all individuals, including individuals with disabilities. As part of this commitment, Wayfair will make reasonable accommodations to the known physical or mental limitations of qualified individuals with disabilities, unless doing so would impose an undue hardship on business operations. If you require a reasonable accommodation to participate in the job application or interview process, please let us know by completing our Accomodations for Applicants form.

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.

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