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zaimler

Posted 4 months ago

Open

MLE, ML Platform

San Mateo, CAOn-siteFull-time

AI Summary

Founding ML engineer who turns enterprise data into structured knowledge graphs and embeddings, building scalable algorithms and models to enable autonomous AI agents.

About this role

About zaimler
AI agents can't reason over data they don't understand. Enterprise data today is fragmented across dozens of systems with no shared context, meaning, or structure, and that's why most enterprise AI is failing. The shift from copilots to autonomous agents is creating an entirely new infrastructure layer, and we're building it.
zaimler is the context infrastructure for the agentic era: a platform that automatically discovers domain knowledge, maps relationships, and gives AI agents the semantic understanding to operate with precision at scale. Imagine knowledge graphs that support real-time inference, built for systems that need to reason, not just retrieve.
zaimler was founded by Biswajit Das (ex-VP Engineering, Truera), a Data Infra veteran and former Chief Architect at Visa, and Sofus Macskassy (ex-Director of Engineering, LinkedIn), who built one of the largest knowledge graphs in production in the industry at LinkedIn. We're growing and deploying with major enterprises across insurance, travel, and technology. If you want to build infrastructure that the next decade of enterprise AI runs on, we'd love to talk.

About the Role

You’ll join our ML team focused on turning raw enterprise data into structured, contextualized knowledge graphs and embeddings. You’ll develop novel and highly scalable algorithms for ML and data engineering to make our overall system more efficient, experiment with new approaches for distilling large models into smaller, more efficient ones; improve retrieval, ranking, and reasoning performance through feedback loops; and prototype methods that help LLMs extract and act on real-world knowledge.

We're looking for someone who thrives on iteration, cares about building with rigor, and is hungry to learn from some of the best engineers and researchers in the field.

What You’ll Be Doing

  • Develop new algorithms and data structures to improve extraction, tagging and resolution
  • Collaborate closely with infra and data engineers to scale your research into production-ready components
  • Prototype and refine models for extracting structured knowledge from text
  • Apply knowledge distillation techniques to compress and optimize LLMs for downstream tasks
  • Explore the use of reinforcement learning and feedback loops for improving model behavior
  • Build evaluation pipelines for entity linking, retrieval, and semantic consistency
  • Read, implement, and build upon recent research in LLM alignment, distillation, and symbolic grounding

    • Prior Experience

  • 2–4 years experience (research lab, internship, academic project, or early industry role) working in ML or NLP
  • Strong fundamentals turning research papers, algorithms and mathematics into scalable and robust C++ code
  • Solid understanding of ML fundamentals: training pipelines, loss functions, evaluation metrics
  • Exposure to knowledge distillation, RLHF, or curriculum learning techniques
  • Strong Python skills and familiarity with ML frameworks like PyTorch or TensorFlow
  • Experience with language models and transformers (e.g., BERT, LLaMA, or similar)
  • A collaborative mindset and willingness to work across research and engineering teams

    • Nice to Have

  • Familiarity with reinforcement learning, including policy optimization or reward modeling
  • Familiarity with using and scaling algorithms to manipulate data, including graph algorithms, text-manipulation, embeddings.
  • Experience with semantic representations such as knowledge graphs or entity embeddings
  • Comfort working with tools like HuggingFace Transformers, Ray, or vLLM
  • Understanding of small-model techniques (pruning, quantization, adapter layers)
  • Interest in the LLM ecosystem and techniques for model alignment or prompt tuning
  • Prior contributions to open-source projects or academic publications in ML/NLP

    • Why Join

  • A rare chance to be a founding engineer shaping both company and product direction.
  • Competitive salary, benefits, and meaningful equity.
  • Work alongside engineers and researchers from LinkedIn, Visa, Meta, and Branch.
  • Onsite culture in San Mateo, designed for deep collaboration and high-velocity building.
  • Full benefits package (Medical, Dental, Vision, 401k).
  • We sponsor H-1B visas and assist with immigration processes.

    • Skills

    C++EmbeddingsEntity LinkingGraph AlgorithmsHuggingFace TransformersKnowledge DistillationKnowledge GraphsPythonPyTorchRayReinforcement LearningRLHFTensorFlowVLLM

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