Responsibilities
- Architect and maintain production-grade image and video generation systems, including inpainting, upscaling, style transfer, and post-processing, with focus on performance, observability, and efficiency.
- Build scalable agentic workflows using frameworks like ADK, A2A, or LangGraph, and develop supporting microservices with tools such as FastAPI or GraphQL.
- Create and manage MCP servers to enable seamless communication between AI agents and services.
- Design structured prompt engineering systems to ensure reliable and repeatable visual outputs, especially for fashion and virtual try-on applications.
- Collaborate with data science teams to implement evaluation-driven quality controls and consistency checks in generative pipelines.
- Integrate vision-language and multimodal models into operational workflows for tasks like image tagging, caption generation, and pre-deployment quality assessment.
- Work closely with product, design, and engineering teams to align generative AI solutions with brand and business goals.
- Conduct proof-of-concept evaluations to assess emerging models, tools, and third-party providers for potential adoption.
- Develop and support full ML infrastructure, covering training, inference, and deployment of generative models in production environments.
Benefits
- Medical insurance
- Dental coverage
- Vision care
- Paid time off
- Employee discounts
- Retirement savings plan
Responsibilities
- Design, build, and optimize image and video generation pipelines (generation, inpainting, upscaling, style transfer, conditioning, post-processing) into production-ready, observable services with attention to cost, latency, and throughput.
- Design and develop agentic workflows (ADK, A2A, LangGraph, or similar), MCP servers (FastMCP or similar), and microservices (FastAPI, GraphQL, or similar) to orchestrate and serve generative AI capabilities at scale.
- Develop prompt management systems and structured prompting strategies for consistent visual output, learning on the job how to wrangle prompts for fashion-specific and virtual try-on use cases.
- Engineer consistency mechanisms and quality gates in partnership with data scientists who own evaluation methodology.
- Integrate multimodal and vision-language models into production workflows for image understanding, automated tagging, captioning, and quality pre-screening.
- Collaborate with Product Designers, Product Managers, Data Scientists, and other Engineers to translate brand and business needs into scalable generative AI solutions.
- Evaluate new technologies, models, and vendors through proof-of-concept studies.
- Implement and maintain ML architecture, including pipelines and applications that enable training and inference of generative models in production.
- Champion best practices in full-stack algorithm engineering.
Benefits
- medical
- dental
- vision
- PTO
- generous employee discounts
- retirement savings
