Senior Machine Learning Engineer - 1
$180k - $240kParspec
About Parspec Founded in 2021, Parspec is revolutionizing material procurement for the $13 trillion USD construction industry by digitizing and organizing the industry's product data. Our proprietary AI technology maintains a current and comprehensive catalogue of millions of products, enabling our customers to identify products that best meet their needs - instantly. Trusted by top designers, builders, distributors and sales agents and backed by leading venture investors, Parspec is paving the way for a more innovative, connected, and sustainable future in construction. Join us in building transformative technology that reshapes one of the world's oldest and largest industries. The Opportunity We are seeking a highly skilled Senior Machine Learning Engineer to join our AI team and play a pivotal role in developing state-of-the-art discovery and extraction systems. As a senior member of the team, you will lead the design, development, and deployment of sophisticated machine learning models, specifically focusing on search ranking, recommendation engines, and high-precision document extraction. You will work on complex data science problems while collaborating closely with business, product, and engineering teams to deliver impactful AI-driven features that are central to our product offering. This is a unique opportunity to be at the forefront of innovation, leveraging advanced AI technologies like LLMs and vector databases to transform an industry ripe for digital disruption. What You Will Achieve and Key Responsibilities 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.
- 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.
- 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.
- 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
- 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.
- 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.
- Competitive salary and discretionary bonus, plus equity options. The pay range for this role is $180-$240K.
- Unlimited PTO policy
- Medical, dental, and vision coverage
- Flexible hybrid work environment
- Regular team offsites and a budget for professional development
- Preferred Location: San Mateo, with regular in-office presence
Vacancy posted 1 day ago
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