Machine Learning Engineer II

Our Opportunity:
Chewy is growing! The Enterprise People Analytics team at Chewy is building advanced AI and machine learning solutions to redefine HR decision-making. As a Machine Learning Engineer (MLE) focused on AI product development, you will design and deploy innovative machine learning models, mentor junior Team Members, and drive the production of scalable AI solutions that empower Chewy's HR function.
This role blends deep technical expertise, critical thinking, and a passion for solving complex HR challenges with machine learning and AI. You'll collaborate with data scientists, engineers, and business intelligence guides to transition research into robust, business-aligned AI products. With a strong focus on unstructured data, dynamic graph analysis, and LLM-backed text analytics, this position offers the opportunity to make a relevant impact on how Chewy attracts, develops, and retains talent. Does this sound like you? We'd love to hear from you!
Key Responsibilities

• Develop and Deploy AI Solutions: Design, implement, and deploy advanced machine learning models to address HR-specific challenges, including talent management, workforce planning, and employee engagement.
• Scalable AI Product Development: Create and maintain long-term development roadmaps for AI solutions, ensuring scalability, maintainability, and alignment with business priorities.
• Research to Production: Collaborate with data scientists, machine learning engineers, and business intelligence engineers to transition research and visualization prototypes into production-grade applications.
• Unstructured Data Analysis: Lead research projects involving unstructured data, including natural language processing (NLP), dynamic graph data, and LLM-backed text analytics to uncover actionable insights.
• Mentorship and Leadership: Provide technical mentorship to junior data scientists, fostering their growth in both technical expertise and discernment.
• Model Evaluation and Monitoring: Implement thorough model evaluation processes and monitoring pipelines to ensure deployed models remain accurate, fair, and reliable over time.
• HR Collaboration: Partner with HR leaders and business teams to align AI efforts with organizational goals and deliver important, actionable insights.

Qualifications

• Technical Expertise: Sophisticated knowledge of machine learning, statistical modeling, and AI methodologies, with hands-on experience in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Experience with Unstructured Data: Strong experience working with unstructured data, including text and dynamic graph datasets.
• Product Development: Track record of design and deploy production-grade AI systems, including scalability and maintainability considerations.
• Cloud and MLOps: Experience with cloud-based environments and familiarity with MLOps tools for model deployment, versioning, and monitoring.
• Eye For Business: Ability to align AI solutions with organizational priorities, translating technical capabilities into business value.
• Mentorship Skills: Consistent track record to mentor junior Team Members, enhancing their technical skills and critical thinking.

Preferred Skills:

• Experience with LLMs and text analytics frameworks.
• Proficiency in dynamic graph analytics tools such as NetworkX or Neo4j.
• Familiarity with monitoring and observability tools for AI pipelines (e.g., MLflow, Prometheus, or Grafana).
• Knowledge of security standard methodologies in AI and ML deployments.

Chewy is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, gender, citizenship, marital status, religion, age, disability, gender identity, results of genetic testing, veteran status, as well as any other legally-protected characteristic. If you have a disability under the Americans with Disabilities Act or similar law, and you need an accommodation during the application process or to perform these job requirements, or if you need a religious accommodation, please contact [email protected].
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