Full-Time

AI Engineer

Updated on 9/12/2026

NeoSigma

NeoSigma

1-10 employees

Autonomous ML engineer automating ML workflows

No salary listed

Bengaluru, Karnataka, India

In Person

Bachelor's

Category
AI & Machine Learning (1)
Required Skills
LLM
Machine Learning
Data Analysis

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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.
  • Ability to work directly with customers and translate their constraints into system decisions.
  • Ability to maintain a high bar for code quality and modular systems that remain clean as they grow.
  • Ability to move quickly in ambiguous territory 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 failures, triaging, evaluations, and optimizations.
  • Design and implement large-scale data processing systems that turn production agent traces into signals for evaluation and optimization.
  • 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.

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