Software Engineer III - Visual AI Technology
Role details
Job location
Tech stack
Job description
Candidates for this position can be based in Toronto, Ontario; Boston, Massachusetts; Mountain View, California; or Seattle, Washington. This is primarily a hybrid role that requires 3 times a week in office, in addition to scheduled team collaboration required at the Wayfair Office in Boston, Massachusetts, up to 4 times per year. The required team core hours are 9am-5pm EST., * System Ownership: Be responsible for making technical decisions related to multiple components of an existing code base / system that is managed by your team / atomic teams.
- Autonomous Execution: While you will be assigned work by your Team Lead (EM/L4+ ICs), you will also make autonomous decisions about prioritizing your work.
- Ambiguous Problem Solving: Solve problems that arise within the components of an existing code base / system managed by your atomic team. You will tackle problems that are more ambiguous because they are scoped (but not defined) for you.
- Pattern Recognition & Improvement: Identify code or design patterns across an existing codebase / system. Ensure the outcome of your work improves multiple components of the codebase / system.
- Cross-Functional Collaboration: Interface with members of adjacent atomic teams within the same pod (eg: PM, XD, Analytics) to align on deliverables.
- Drive Measurable Impact: Have a measurable business impact downstream on team members and the codebase within your atomic team, and upstream within your pod.
- Build & Deploy: Design scalable and resilient microservices that interface with external APIs and internal models, containerizing applications using Docker and managing services in Kubernetes (pods, services, ConfigMaps, secrets).
- Actively utilize AI-powered developer tools (e.g., Cursor, Co-Pilot, Google AI Suite) to enhance coding productivity and efficiency.
Requirements
Do you have experience in Unsupervised learning?, * A solid understanding of Machine Learning fundamentals (e.g., supervised vs. unsupervised learning, model evaluation metrics) and experience with common ML libraries/frameworks (e.g., PyTorch, TensorFlow, Scikit-learn).
- Familiarity with fine-tuning or serving large models (e.g., LLMs, diffusion models) and experience working with APIs for ML services (e.g., OpenAI, RunwayML, HuggingFace, Fal.ai).
- Strong Python skills (experience with FastAPI or Flask is a bonus) and a solid understanding of cloud platforms (GCP/AWS/Azure) for compute-heavy workloads.
- Comfort consuming and exposing REST and/or GraphQL APIs, along with experience using authentication methods (OAuth, API keys, JWT).
- Familiarity with writing unit and integration tests, CI/CD tools (e.g., Buildkite, GitHub Actions, Jenkins), and monitoring production systems (observability: logs, metrics, tracing).
- An understanding of data preprocessing pipelines for ML input/output, and experience working with both structured and unstructured data (images, text, video).
- Familiarity with data storage solutions like GCS, PostgreSQL, BigQuery, or MongoDB.
- Proficiency with React, building interactive UIs, and frontend state management (e.g., Redux, Zustand)., * Experience with model optimization or quantization for deployment.
- Understanding of model lifecycle management (MLflow, Weights & Biases).
- Some DevOps experience (Terraform, Helm, ArgoCD).
- Experience with GPU-enabled workloads and scheduling in Kubernetes.
- Previous experience in a 3D content pipeline (e.g., architectural visualization, games, VFX workflows).
- Experience building interactive UIs using React and modern frontend practices for ML-powered tools, integrating securely with backend APIs and authentication layers.
Benefits & conditions
Pulled from the full job description
- Tuition reimbursement
- Parental leave
- Health insurance
- 401(k) matching
- Paid time off
- Employee discount
- Vision insurance