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Salary
$150k – $200k per year
Location
In office (Palo Alto)
Seniority
Junior · 1+ year exp
Employment
Full-Time
Overview
Company
Impact
Profile match
Turing Labs is a Y Combinator and Insight Partners-backed AI software platform engineered to accelerate product development, formulation, and regulatory compliance for Consumer Packaged Goods (CPG) companies. Its proprietary "Growth OS" leverages domain-trained AI agents - including its Luna optimization engine - to unify commercial strategy, formulation histories, financial targets, and ingredient safety standards within a single predictive system.

We’re looking for a fantastic, high-agency problem solver to originate our forward deployed engineer team.

Turing Labs is transforming product and R&D innovation across the Consumer Packaged Goods space and beyond. Our founders started Turing after seeing how 90% of CPG innovations fail due to slow, manual R&D cycles-we’re fixing that with math. Leveraging our own bespoke Machine Learning tools, modern LLMs, and traditional software, we’re building product experiences that users are able to leverage and trust while they invent the products of tomorrow. You’ll work directly with the founder, food science domain experts, ex-math professors, and our customers to help users solve problems and remove anything that blocks great ideas from becoming reality.

If you think you’d be a good fit but don’t necessarily meet the profile below, **reach out and tell us why!**

What you'll do:

  • Embed deeply with customers, with an eye for both problem solving and productizing common issues.
  • Identify and automate product insights to drive our company’s direction.
  • Solve customer problems with our software, machine learning, and AI toolkit, and leverage our AI-assisted tooling and workflows to build custom software and agents on top of this core code where it falls short
  • Within 15 days: understand one key problem facing a user and propose a fix; Within 30 days: deliver a custom implementation layer that solves a specific user problem the core tooling does not; Within 60 days: embed on-site with a customer for a week to watch, identify, and solve user problems we can’t see from our office.

A good fit likely has:

  • Experience in one or more of: forward deployed engineering, product, ML / AI, and food science / chemical engineering; as well as comfort having a semi-technical conversation about those fields in which you don’t have experience
  • A knack for identifying and quantifying measurable outcomes.
  • An uncanny ability to identify root causes vs surface level problems
  • Excellent communication and candor. You’ll be directly communicating with customers, users, engineers, domain experts, etc.
  • Proven high-ownership mindset: ability to work independently and be self-motivated, e.g. former founders or those that took extreme ownership in previous roles.

This might not be for you if:

  • You rely on central, rigid processes or heavy structure to identify problems.
  • You prefer pure relationship / account management without technical implementation.

It’s a bonus if you have:

  • Specific education in chemistry, physics, machine learning, AI, etc
  • Product / UX experience. You’ll be building things non-technical users touch, use, and rely on every day.

About us:

  • We are backed by $19.75M in funding from Y Combinator, Insight Partners, and elite angels like Eric Ries.
  • Our core platform can’t be killed by the next release of ChatGPT.
  • We are a small, elite team that is breaking new ground in how engineering work can be done and how problems can be solved.
  • We operate with a high agency, high-speed culture: we trust you, we want you to build great things fast.

This position is based in Palo Alto, CA with some travel expected.

Step 1 - 30 minute phone screen to confirm fit. We are looking for people with strong ownership mentality and problem-solving skillsets, and want to know how you’ve demonstrated that.

Step 2 - 75 minute problem-solving interview. Use any tools you want. We will adapt topic based on in-person vs virtual. This interview will be split equally between problem identification skills and building a solution to small hypothetical scenario.

Step 3 - Meet anyone you haven’t met yet! We’re a small team and want to make sure we all get along.

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