Machine Learning Software Engineer, Customer Service Technology

Vollzeit
Boston, MA, USA
vor 8 Monate

Job Description

 

Machine Learning Software Engineer, Customer Service Technology

 

Candidates for this position are required to be based in Boston, MA and will be expected to comply with their team's hybrid work schedule requirements.

 

Who We Are:

Wayfair's customer service machine learning team is a specialized unit within the organization, tasked with harnessing the power of machine learning algorithms to revolutionize customer support pipelines and tooling. Composed of ML engineers, ML scientists, and domain experts, this team is at the forefront of developing and deploying ML-driven solutions that optimize various aspects of the customer service journey. From automating routine inquiries through chatbots to predicting customer needs and preferences for more tailored assistance, our focus lies in creating scalable and efficient models that enhance both agent productivity and customer satisfaction. With a deep understanding of both the technical intricacies and the customer service landscape, we continuously iterate and innovate to deliver increasingly sophisticated ML solutions that anticipate and exceed customer expectations.

 

We are looking for a passionate senior machine learning engineer to join the team to partner with us to extend our existing set of traditional ML technologies and infrastructure and to help us blaze a path in the generative AI space. Our products are specifically designed to interact with customers during their live contacts with Wayfair. The MLE team supports structured data models, NLP models, and LLM technology through a set of cloud-hosted infrastructure to serve billions of requests in a fully online, monitored framework.

 

Why will you like the team you are joining?

  • We work with cutting edge technology (we were the first team at Wayfair to put an LLM-based application into production)
  • We won a company-wide technology award in 2023
  • We do fun team activities like Boda Borg, kayaking the Charles, and mini golf

 

Interested in learning more about Wayfair’s Engineering community? 

  • How Vertex AI Endpoints helped Wayfair achieve real-time model serving
  • How Wayfair is improving its feature engineering system with Vertex AI
  • Wayfair’s ML technology blog: https://www.aboutwayfair.com/tag/machine-learning-ai 
  • Graham Ganssle Customer Service ML Team Lead

 

What You’ll Do:

  • Research and experiment with state-of-the-art generative AI techniques and algorithms, and evaluate their performance on benchmark datasets and real-world scenarios.
  • Assist in the design, development, and implementation of advanced machine learning infrastructure and algorithms to solve complex business problems.
  • Collaborate with cross-functional teams to gather requirements, define project objectives, and identify opportunities for applying machine learning techniques.
  • Conduct exploratory data analysis to gain insights into the underlying patterns and relationships within the data, and identify features for model training.
  • Develop and deploy machine learning models in production environments, and monitor their performance to ensure reliability, scalability, and accuracy over time.
  • Optimize and fine-tune machine learning infrastructure for performance, scalability, and efficiency, and implement techniques for model interpretability and explainability.
  • Provide technical guidance and expertise, and foster a culture of innovation and continuous learning within the team.
  • Stay updated with the latest advancements in machine learning research and technologies, and actively contribute to the development of best practices and standards within the organization.
  • Collaborate with product managers, engineers, and stakeholders to translate business requirements into technical solutions, and communicate the impact of machine learning projects on business outcomes.
  • Change our systems and platforms to increase efficiency, reduce costs, increase stability, reduce technical debt and as a result increase revenue working closely with our product partners & operations partners.
  • Solve a wide range of challenging business problems in customer service and global partner support that extend the competitive advantage which separates Wayfair from other online retailers
  • Contribute to architectural and code review discussions impacting our engineering ecosystem

 

We Are a Match Because You Have:

  • Extensive experience in applying machine learning techniques to real-world problems, with at least 4 years of relevant industry experience.
  • Deep understanding of advanced machine learning algorithms and techniques, including deep learning, reinforcement learning, generative AI, and transfer learning.
  • Proficiency in multiple programming languages such as Python, or Java, with expert-level knowledge of Python preferred.
  • Expertise in popular machine learning frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or Keras, with the ability to design and implement complex models from scratch.
  • Proven track record of delivering successful machine learning projects from conception to deployment in a production environment.
  • Strong software engineering skills, including proficiency in writing clean, modular, and maintainable code, as well as familiarity with software design patterns and best practices.
  • Experience with distributed computing frameworks for handling large-scale datasets and training models in parallel.
  • Deep understanding of data engineering concepts and experience with building scalable data pipelines for collecting, processing, and transforming data.
  • Proficiency in cloud computing platforms, preferably Google Cloud, with experience deploying and managing machine learning models in cloud environments.
  • Strong analytical and problem-solving skills, with the ability to quickly understand complex systems and propose innovative solutions.
  • Excellent communication skills, with the ability to collaborate effectively with cross-functional teams.
  • Demonstrated ability to stay updated with the latest advancements in machine learning research and apply them to solve business problems effectively.
  • Bachelor’s degree in Computer Science, Computer Engineering or equivalent combination of education and experience
  • Experience working with relational and non-relational databases

 

Why You’ll Love Wayfair:

  • 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 

We are looking forward to your application!

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.

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