AI Machine Learning Engineer (ID: 0I7UMea1)

AI Engineer – Agentic Systems & RAG - Looking for an experienced AI Engineer to design and build our next generation of agent-powered products. In this role, you’ll develop, evaluate, and scale sophisticated Retrieval-Augmented Generation (RAG) pipelines and agentic workflows that unlock new, intuitive ways to shop.

Our LLM-powered agents leverage a rich set of tools to interact with customer catalogs, perform advanced retrieval, and guide users through browsing and discovery. The result: accurate, well-cited answers and exceptional product recommendations for open-ended user queries.

What You’ll Do

• Design and implement real-time, agentic workflows that handle complex, multi-step user tasks and open-ended queries
• Build systems that deliver accurate, context-aware responses and high-quality product recommendations
• Own the end-to-end data lifecycle for AI workflows, including vector ingestion, indexing, and retrieval
• Define and implement evaluation metrics to measure relevance, performance, and alignment with business and user goals
• Rapidly prototype and validate new product ideas using LLMs, RAG, and agent-based systems
• Collaborate closely with Product, Design, Analytics, and Engineering partners to turn AI capabilities into polished product features
• Continuously improve the speed, quality, reliability, and efficiency of our AI systems
• Take ownership of systems from initial design through deployment, monitoring, and long-term maintenance

What We’re Looking For

• 4+ years of industry experience in areas such as search, information retrieval, recommendation systems, applied ML, or NLP
• Strong ability to communicate technical work in terms of business impact
• Proficiency in Python and SQL, with hands-on experience building end-to-end ML or LLM-powered systems
• Deep understanding of information retrieval techniques (e.g., dense retrieval, re-ranking, chunking strategies)
• Practical experience building Retrieval-Augmented Generation (RAG) systems; experience with autonomous agents is a strong plus
• Familiarity with ML evaluation methodologies and core IR metrics

Nice to have:

• experience with automated prompt optimization techniques (e.g., DSPy)
• A product-oriented mindset, strong ownership mentality, and passion for shipping high-quality work

Tech Stack

• Core: Python, FastAPI, asyncio, Airflow, Luigi, PySpark, Docker, LangGraph
• Data Stores: Vector databases, DynamoDB, AWS S3, AWS RDS
• Cloud & MLOps: AWS, Databricks, Ray

Benefits & Perks

• Unlimited vacation time (we encourage everyone to take at least 3 weeks per year)
• Fully remote team, work from anywhere
• Work-from-home stipend to support your home office setup
• Apple laptop provided
• Annual training and professional development budget
• Maternity and paternity leave for eligible employees
• Regular team offsites to connect and collaborate
• Work alongside smart, supportive teammates and make a meaningful impact

Compensation:

This role has a base salary range of $80,000–$120,000 USD, depending on experience, skills, and interview performance.