Job Details

Location: San Mateo, CA (hybrid 2 days onsite a week)

AI System Development

• Search & Recommendation Systems

  Lead the design and implementation of advanced Search, Ranking, and Recommendation systems to help customers navigate millions of technical products.

  
  

• Doc Extraction & NLP

  Develop high-precision NLP and document extraction pipelines to digitize and structure complex construction data from unstructured sources.

  
  

• Advanced Architecture

  Research and implement novel deep learning architectures, focusing on hybrid retrieval models and fine-tuned LLMs.

  
  

• Production Deployment

  Develop, train, and deploy deep learning and machine learning models that are scalable, extensible, and integrated into production environments.

  
  

• Agentic Workflows

  Architect autonomous or semi-autonomous agents that can plan and execute multi-step discovery tasks.

  
  

Full Product Lifecycle Participation

• Technical Leadership

  Collaborate with product managers and UX designers to integrate AI components into fully functional systems, providing technical guidance on feasibility and architecture.

  
  

• End-to-End Ownership

  Participate in the complete product lifecycle—from concept design to development, integration, testing, and deployment.

  
  

Scalable Solutions

• High-Volume Data

  Build products that handle large data volumes efficiently while remaining highly scalable for onboarding new clients.

  
  

• Pipeline Design

  Design complete end-to-end data and ML pipelines, ensuring seamless integration and monitoring in production.

  
  

Research & Collaboration

• R&D Initiatives

  Work closely with the leadership team on research efforts to explore cutting-edge technologies, such as vector databases and embedding-based retrieval.

  
  

• Excellence Standards

  Uphold a culture of engineering excellence by maintaining high standards in code quality, documentation, and innovation

  
  

Minimum Qualifications

• Education

  Bachelor's or Master's degree (PhD preferred) in Science or Engineering with strong programming and analytical skills.

  
  

• ML Expertise

  Strong conceptual understanding of machine learning principles, specifically in NLP, Search, or Ranking.

  
  

• Technical Skills

  Hands-on experience implementing ML projects in Python using libraries like NumPy, scikit-learn, and pandas.

  
  

• Deep Learning

  Proficiency in training and fine-tuning deep learning models using PyTorch or TensorFlow.

  
  

• Leadership

  Proven ability to lead technical initiatives from concept to operation while navigating complex challenges.

  
  

Preferred Qualifications

• Specialized Infrastructure

  Deep experience with

  
  

  Vector Databases (e.g., Pinecone, Milvus) and optimizing embedding models for retrieval.
• Fine-tuning

  Experience fine-tuning LLMs for specialized domain tasks and ranking signals.

  
  

• AI Agent Orchestration

  Hands-on experience with agentic frameworks (e.g., LangGraph, AutoGen, or CrewAI) for building complex, multi-step reasoning chains.

  
  

• Planning & Memory

  Experience implementing agentic "memory" (long-term/short-term) and planning strategies (like ReAct or Tree of Thoughts).

  
  

• Data Structures

  Expert knowledge of algorithms and data structures.

  
  

• Research & Community: A track record of publications in top-tier conferences (e.g., NeurIPS, SIGIR, KDD, ACL) or significant contributions to open-source ML projects.