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NeoSigma

Autonomous ML engineer automating ML workflows

Product Design Engineer

Full-TimeUpdated on 10/25/2026
No salary listed
Mid
Bachelor's
San Francisco, CA, USA
In Person
Software EngineeringFrontend Engineering
H1B Sponsorship Available

About the job

Requirements
  • Strong frontend engineering experience building complex, production-quality applications in React and TypeScript.
  • Exceptional product instincts, with a high degree of ownership from problem definition through execution.
  • Strong visual taste across typography, layout, interaction, motion, and overall product aesthetics.
  • Experience building developer tools, data-intensive products, or sophisticated visualizations and interfaces.
  • Comfortable working directly with customers and turning their feedback into better product experiences.
  • Able to operate fluidly across engineering, product, and design, owning outcomes without unnecessary handoffs.
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent experience.
Responsibilities
  • Build the developer experience that makes complex AI systems intuitive and easy to understand.
  • Own the interfaces, visualizations, and interactions that help customers understand and improve their AI systems.
  • Work directly with customers and the engineering team to turn complex technical workflows into polished, developer-first product experiences.
  • Help define the visual language, interaction patterns, and product experience of the product.
  • Own the developer product end to end, from customer problems to designing and shipping the experience in production.
  • Build technically sophisticated, production-quality interfaces in React and TypeScript.
  • Design rich visualizations and interactions that make complex AI systems, data, and workflows intuitive.
  • Work closely with customers to understand product usage and turn those insights into better product decisions.
  • Prototype, iterate, and ship new experiences quickly, moving between engineering, design, and product.
  • Own the design system and frontend foundations.
  • As a founding team member, help define the technical foundation of the company; scope may grow to owning core systems, shaping architecture, hiring, and engineering culture as the company scales.

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