Member of Technical Staff - AI Engineer

Status
Open
Remote policy
Remote
Employment type
Not stated
Salary
Not stated
Categories
AI-Engineer, Machine-Learning-Engineer, Software-Engineer, Research-Engineer, Staff-AI-Engineer, Staff-Applied-AI-Engineer, Staff-AI-Software-Engineer, Staff-ML-Engineer, Staff-AI-ML-Engineering, Staff-AI-Engineering, Staff-Machine-Learning-Engineer, AI-Technical-Specialist
Tech
remote-countrysoftwarestaff
Source
himalayas
First observed
2026-09-27 08:10 UTC
Last seen
2026-09-27 08:10 UTC
Source claims posted
2026-09-27 08:03 UTC
Consecutive misses
0 of 10

What the posting says

About Us

NeoSigma is a product-driven research lab building the intelligence layer that helps close the feedback loop between your customers, products, and AI systems.

We are a small, intensely technical team of researchers and engineers who have trained frontier-scale models and widely used AI products and agents at MIT, Parallel Web, Essential AI, Apple, and Amazon.

We are backed by world-class investors and leaders from Google DeepMind, OpenAI, Decagon and others.

The Role

We are looking for a AI Engineer to build intelligent systems that learn from real-world usage. You will work across LLMs, agent architectures, evaluation pipelines, and production AI systems, turning cutting-edge research into reliable products. Some weeks you'll be developing novel AI capabilities and experimenting with new models. Other weeks you'll be shipping production features that help customers build smarter, more reliable AI applications.

What you'll do

Build SOTA agentic pipelines that mine production traces for failures mining, triaging, evaluations, and optimizations

Design and implement large-scale data processing systems that turn production agent traces into signal for evaluation and optimization

Design and run optimization loops that convert evaluation signal into measurable gains in agent behavior

Own the cost and latency profile of our ML systems as trace volume and customer count scale

Push novel evaluation and post-training research into production within weeks

What we look for

Hands-on experience shipping LLM-powered or agentic systems to real production environments

Strong instincts around evaluation design, post-training methods, and agent triaging

Comfortable working directly with customers and translating their constraints into system decisions

High bar for code quality, modularity, and systems that stay clean as they grow

Ability to move fast 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)

Our Core Values

Customer Obsession - We start with the customer and work backwards. We aim to earn trust through consistent delivery, thoughtful listening, and by obsessing over customers.

Intellectual Honesty - We operate with high trust and low ego. Ideas matter more than titles, and we communicate openly and directly while assuming good intent, even in strong disagreement.

Bias for Action - We set high standards and move quickly to meet them. We prefer building and learning with customers over debating in the abstract, and we iterate based on real feedback.

Extreme Ownership - We take responsibility for outcomes, not just tasks. Ownership means seeing problems through to completion and ensuring solutions truly work in practice.

Benefits and perks

Competitive salary plus meaningful equity package

Comprehensive medical benefits and generous PTO

Flexible work arrangements

Direct impact on company direction and technical decisions

High ownership and the opportunity to make a career-defining impact

As a founding member, you’ll help define the technical foundation of NeoSigma. Your scope will grow with the company, from owning core systems end-to-end to shaping architecture, hiring, and engineering culture. This role has a natural path toward technical leadership or engineering management as the team scales.

Originally posted on Himalayas

Quality

Completeness: 65%

Not enough history yet to judge honesty signals.

Timeline

  1. *
    #1027780 2026-09-27 08:10 UTC
    Published