Software Engineer II

Chewy Chewy · Retail · Boston, MA

Software Engineer II at Chewy focused on building and scaling platforms for Data Science and AI capabilities, including data pipelines, ML platforms, and serving infrastructure. The role involves supporting ML model training, evaluation, and deployment, with an emphasis on AI-assisted engineering and LLM integration.

What you'd actually do

  1. Design and build scalable data pipelines (ETL/ELT) and services that support training, evaluation, and deployment of machine learning and AI models
  2. Develop and maintain ML platforms and tooling for experimentation, simulation, and production model serving
  3. Implement data ingestion, transformation, and validation workflows to ensure high-quality, reliable datasets for modeling
  4. Contribute to Spec-Driven Development (SDD) practices by translating requirements into testable specifications and automated validation workflows
  5. Leverage AI developer tools and LLM-assisted workflows to accelerate development, testing, and debugging

Skills

Required

  • Python development
  • data and ML libraries (e.g., pandas, PySpark, scikit-learn, PyArrow)
  • ETL/data pipelines
  • large-scale datasets
  • SQL
  • data modeling
  • data transformations
  • data quality
  • cloud platforms (AWS preferred)
  • distributed data processing systems
  • software engineering fundamentals (OOP, data structures, testing, version control)
  • machine learning workflows
  • model lifecycle management
  • fast-paced environment
  • ownership of deliverables

Nice to have

  • LLMs
  • generative AI
  • prompt engineering
  • SSD
  • AI-assisted development tools (e.g., Copilot, Claude, GPT-based workflows)
  • Spec-Driven Development (SDD) or test/spec-first development approaches
  • MLOps tooling (MLflow, Airflow, Kubeflow, SageMaker, etc.)
  • data pipelines with Spark, Airflow, or similar orchestration tools
  • containerization and orchestration (Docker, Kubernetes)
  • CI/CD pipelines
  • automated testing frameworks
  • model validation
  • monitoring
  • production reliability practices
  • agile environment (Scrum, Kanban)

What the JD emphasized

  • 3–5 years of experience in Python development
  • Hands-on experience building and maintaining ETL/data pipelines
  • Experience with SQL
  • Experience with cloud platforms (AWS preferred)
  • Exposure to machine learning workflows and model lifecycle management

Other signals

  • build and scale platforms that power Chewy’s Data Science and AI capabilities
  • develop, evaluate, and deploy machine learning and generative AI solutions at scale
  • infrastructure supporting forecasting, optimization, experimentation, and real-time decision-making
  • evolve our development practices toward Spec-Driven Development (SDD) and AI-assisted engineering
  • Design and build scalable data pipelines (ETL/ELT) and services that support training, evaluation, and deployment of machine learning and AI models
  • Develop and maintain ML platforms and tooling for experimentation, simulation, and production model serving
  • Build and integrate APIs, microservices, and orchestration pipelines for end-to-end ML lifecycle management
  • Participate in building next-generation solutions using LLMs, prompt engineering, and retrieval-augmented generation (RAG) patterns