Beacon
Staff Machine Learning Engineer
Beacon, San Francisco, CA, United States
Founding/Staff Machine Learning Engineer - Generative AI
Our client is a venture-backed YC startup revolutionizing the supply chain sector with cutting-edge generative AI technologies. As a rapidly growing organization, they are applying advancements in machine learning to address complex industry challenges, unlocking unprecedented efficiencies and insights for their clients.
Role Overview
We are seeking a Founding/Staff Machine Learning Engineer with deep expertise in generative AI to lead critical technical efforts in developing and deploying state-of-the-art solutions. This role is for an experienced engineer who thrives on building robust, scalable systems and is passionate about advancing the frontiers of AI. This position requires hands-on experience in training large language models (LLMs), working with embedding models and vector databases, and developing AI-powered chatbot solutions.
Key Responsibilities
Our client is a venture-backed YC startup revolutionizing the supply chain sector with cutting-edge generative AI technologies. As a rapidly growing organization, they are applying advancements in machine learning to address complex industry challenges, unlocking unprecedented efficiencies and insights for their clients.
Role Overview
We are seeking a Founding/Staff Machine Learning Engineer with deep expertise in generative AI to lead critical technical efforts in developing and deploying state-of-the-art solutions. This role is for an experienced engineer who thrives on building robust, scalable systems and is passionate about advancing the frontiers of AI. This position requires hands-on experience in training large language models (LLMs), working with embedding models and vector databases, and developing AI-powered chatbot solutions.
Key Responsibilities
- Train and fine-tune LLM foundation models (e.g., GPT, Claude, PaLM 2, LLaMA) using cutting-edge techniques and frameworks, ideally on AWS SageMaker.
- Design, implement, and optimize embedding models for a variety of applications.
- Build and deploy AI-powered chatbots using frameworks like LangChain or LangGraph.
- Integrate and manage vector databases (e.g., MongoDB Atlas Vector Store, Milvus, Weaviate, Pinecone) to support efficient model querying and retrieval.
- Collaborate closely with cross-functional teams to align AI-driven solutions with business objectives in the supply chain domain.
- Write clean, maintainable, and scalable code in Python; TypeScript experience is a strong plus.
- Drive the end-to-end lifecycle of machine learning models, from research and experimentation to production deployment and monitoring.
- Experience: 5+ years of hands-on experience as a Machine Learning Engineer (not a Data Scientist) with a focus on developing and deploying production-ready solutions.
- Foundation Models: Proven experience training and fine-tuning LLMs (GPT, Claude, Gemini/PaLM 2, LLaMA, etc.).
- Embedding Models: Strong expertise in designing and implementing embedding-based solutions.
- Vector Databases: Practical knowledge of vector databases (MongoDB Atlas Vector Store, Milvus, Weaviate, Pinecone, etc.).
- Chatbots: Hands-on experience building AI-powered chatbots, ideally using LangChain or LangGraph.
- Technical Skills: Advanced proficiency in Python. Experience with TypeScript is a plus but not required.
- Cloud Platforms: Familiarity with AWS, particularly SageMaker, for training and deploying models.
- Team Collaboration: Excellent communication and collaboration skills to work in a fast-paced, multidisciplinary environment.
- Be a foundational team member in a high-impact, venture-backed startup.
- Solve meaningful problems with cutting-edge generative AI technologies.
- Work in a dynamic, collaborative environment in the heart of Silicon Valley.
- Enjoy competitive compensation, benefits, and equity opportunities.