Winter 2026

Member of Technical Staff Intern

Updated on 9/15/2026

NeoSigma

NeoSigma

1-10 employees

Autonomous ML engineer automating ML workflows

No salary listed

San Francisco, CA, USA

In Person

Bachelor's, Master's, PhD

Category
AI & Machine Learning (1)
Required Skills
LLM

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Requirements
  • Currently pursuing a Bachelor's, Master's, or PhD in Computer Science, Machine Learning, Engineering, or a related field.
  • Hands-on experience building large language model-powered or agentic systems in production or research settings.
  • Strong research judgment, especially in evaluation design, post-training methods, and model improvement workflows.
  • Ability to own problems end-to-end, from initial idea to shipped artifact.
  • Attention to detail across research rigor, code quality, and clean modular design.
  • Ability to work directly with a small, fast-moving team.
Responsibilities
  • Design and implement large language model-powered systems and scalable agentic workflows in production.
  • Work on open-ended problems in self-improving artificial intelligence, including agentic systems, automated evaluations, verifier research, and benchmarks.
  • Build robust data-processing pipelines for evaluation datasets and feedback loops.
  • Run experiments, iterate quickly, and move 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.

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 Jobs

Simplify's Take

What believers are saying

  • March 2026 auto-harness results showed Tau3 performance rising from 0.56 to 0.78.
  • July 2026 posts show active partnerships with Daytona and Exa around agent infrastructure.
  • Careers and founder posts in 2026 show hiring momentum and backing from Jeff Dean, OpenAI, and DeepMind leaders.

What critics are saying

  • NeoSigma is still in stealth, so revenue, customers, and retention remain unproven.
  • Its value depends on production agent adoption; OpenAI and Google can bundle similar tooling fast.
  • If sandbox-driven agent maintenance commoditizes, NeoSigma becomes a feature, not a company.

What makes NeoSigma unique

  • NeoSigma builds self-improving agent infrastructure, not just another chatbot, per March 2026 blog.
  • Its sandboxed workspaces mirror developer environments, with Docker, repos, networking, and reproducibility.
  • The company markets production feedback loops that mine failures into reusable evals and harness fixes.

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Benefits

Health Insurance

Paid Vacation

Flexible Work Hours

Company Equity