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NeoSigma

Autonomous ML engineer automating ML workflows

AI Engineer

Full-TimeUpdated on 10/25/2026
No salary listed
Mid
Bachelor's
Bengaluru, Karnataka, India
In Person
Software EngineeringAI Application Engineering

About the job

Requirements
  • Hands-on experience shipping large language model-powered or agentic systems into production environments.
  • Strong instincts in evaluation design, post-training methods, and agent triaging.
  • Comfort working directly with customers and translating their constraints into system decisions.
  • High standards for code quality, modularity, and maintainable systems.
  • Ability to work quickly in ambiguous contexts and turn open problems into clear, executable plans.
  • Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Responsibilities
  • Build state-of-the-art agentic pipelines that mine production traces for failure mining, triaging, evaluations, and optimizations.
  • Design and implement large-scale data processing systems that turn production agent traces into evaluation and optimization signals.
  • Design and run optimization loops that convert evaluation signals 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.
  • Develop novel artificial intelligence capabilities and experiment with new models, as well as ship production features that help customers build smarter, more reliable artificial intelligence applications.

About the company

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

N/A

Total Funding

N/A

Headquarters

San Francisco, California

Founded

2025

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Simplify's Take

What believers are saying

  • NeoSigma published three technical posts between March and September 2026, proving fast execution.
  • The company claims backers include Jeff Dean, OpenAI, DeepMind, Mercor, Decagon, and World Labs leaders.
  • Open roles across San Francisco and Bengaluru show expansion into engineering, product, and GTM.

What critics are saying

  • Daytona's February 2026 Series A and Cloudflare's April 2026 sandbox entry squeeze NeoSigma's moat.
  • NeoSigma's public footprint stays tiny: LinkedIn shows 1-10 employees, founded 2025.
  • If agents stop needing custom feedback infrastructure, NeoSigma's core product becomes irrelevant by 2027.

What makes NeoSigma unique

  • NeoSigma targets production feedback loops, not generic model training, as of September 2026.
  • Its July 17, 2026 Workspaces article shows isolated sandbox infrastructure for autonomous agents.
  • Gauri Gupta markets NEO as an autonomous ML engineer for end-to-end workflow automation.

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Benefits

  • Health Insurance
  • Paid Vacation
  • Flexible Work Hours
  • Company Equity