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Staff Machine Learning EngineerDiligente Technologies • United States
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Staff Machine Learning Engineer

Diligente Technologies
  • US
    United States
  • US
    United States
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À propos

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.
  • United States

Compétences linguistiques

  • English
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