Job Title: Lead AI / ML Engineer
Location: San Francisco Bay area, CA (Hybrid)
Duration: Long term
Tax Term:- W2
Job Summary
Key Responsibilities
Design, build, and maintain scalable AI/ML systems and APIs using Python and Fast API.
Develop and deploy sophisticated applications leveraging Large Language Models (LLMs) with frameworks like Lang Chain and LangGraph.
Architect and implement robust data and ML pipelines on Google Cloud Platform (Google Cloud Platform), utilizing services like Vertex AI, Big Query, Pub/Sub, and Cloud Storage.
Work with large-scale datasets, performing data analysis and manipulation with tools like Pandas, NumPy, and SQL. Integrate with and manage data from various database systems, including PostgreSQL, using libraries like SQL Alchemy and asyncpg.
Write clean, high-quality, and well-tested code, and contribute to a culture of software development best practices.
Collaborate with cross-functional teams to understand requirements and deliver impactful AI-driven features.
Stay current with the latest advancements in AI, machine learning, and cloud technologies to drive innovation within the team.
Required Qualifications
Proven experience in a hands-on software engineering or ML engineering role. Strong programming proficiency in Python (3.10+).
Hands-on experience with Google Cloud Platform (Google Cloud Platform), especially with AI/ML services (Vertex AI, AI Platform) and data services (Big Query, Cloud Storage).
Demonstrable experience building applications with LLMs using frameworks such as Lang Chain.
Experience developing and deploying production-grade APIs using Fast API, Flask, or a similar web framework.
Proficiency in data manipulation and analysis using Pandas and NumPy. Solid understanding of SQL and experience with relational databases (e.g., PostgreSQL).
Preferred Qualification
Experience with LangGraph for creating agentic and stateful LLM workflows.
Familiarity with asynchronous programming in Python (asyncio).
Experience with event-driven architectures and messaging systems like Google Cloud Pub/Sub. Knowledge of MLOps principles and CI/CD practices.
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