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NeoSigma

Autonomous ML engineer automating ML workflows

Member of Technical Staff Intern

InternshipUpdated on 10/25/2026
No salary listed
San Francisco, CA, USA
In Person
Software EngineeringAI Application Engineering

About the job

Requirements
  • Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Engineering, or a related field.
  • Have hands-on experience building LLM-powered or agentic systems in production or research settings.
  • Have research judgment, especially in evaluation design, post-training methods, and model improvement workflows.
  • Be able to own problems end-to-end, from the initial idea through to a shipped artifact.
  • Apply attention to detail across research rigor, code quality, and clean modular design.
  • Be comfortable working directly with a small, fast-moving team.
Responsibilities
  • Design and implement LLM-powered systems and scalable agentic workflows in production.
  • Work on open-ended problems in self-improving AI, including agentic systems, automatic evaluations, verifier research, and benchmarks.
  • Build robust data processing pipelines for evaluation datasets and feedback loops.
  • Run experiments, iterate quickly, and develop ideas from hypothesis to working system.
  • Work closely with customers and the core team to understand workflows and deliver meaningful impact.
  • Publish findings through technical blogs, research papers, or open artifacts that strengthen the technical foundation.

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