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NeoSigma

Autonomous ML engineer automating ML workflows

AI Engineer

Applied Machine LearningUpdated on Nov 14
Full-timeSan Francisco, CA, USAIn-person

About the Job

Requirements

  • Hands-on experience shipping large language model-powered or agentic systems to real production environments.
  • Strong instincts around evaluation design, post-training methods, and agent triaging.
  • Comfort working directly with customers and translating their constraints into system decisions.
  • Ability to maintain high code quality, modularity, and systems that remain clean as they grow.
  • Ability to move quickly in ambiguous territory and turn open problems into clear, executable plans.
  • A bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

Responsibilities

  • Build agentic pipelines that mine production traces for failures, triaging, evaluations, and optimizations.
  • Design and implement large-scale data processing systems that turn production agent traces into signal for evaluation and optimization.
  • Design and run optimization loops that convert evaluation signal into measurable gains in agent behavior.
  • Own the cost and latency profile of machine learning systems as trace volume and customer count scale.
  • Push novel evaluation and post-training research into production within weeks.

About the Company

NeoSigma

Autonomous ML engineer automating ML workflows

NeoSigma builds an AI product lab behind an intelligent automation layer called NEO. NEO acts as an autonomous ML engineer that handles the full machine learning workflow: data science tasks, model training, fine-tuning large language models, building retrieval-augmented generation pipelines, running evaluations, and deploying production-ready AI systems. It works by using multiple agents in parallel inside a GPU sandbox to run hundreds of experiments, measure their performance against targets, and pick the best models. Users can interact with NEO via a chat interface to guide exploration and provide context. NeoSigma can fix training pipelines, add new AI features to existing projects, and check for data leakage in pipelines. The goal is to connect customers, products, and AI systems by delivering automated, end-to-end ML development that speeds up building and deploying AI-powered products.

Company size
1-10
Company stage
Not listed
Total funding
Not listed
Headquarters
San Francisco, CA
Founded
2025

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