Build a better sustainable world!

“Turing Labs is building the Palantir for the CPG industry” - Forbes

Consumer packaged goods (CPG) companies all over the world – including names you already have in your fridge, toiletries bag, make-up case, and pantry – rely on Turing’s AI technology to create new products faster, safer, smarter, and leaner. With our industry-leading platform, we leverage data and combine industry-specific AI technology to create new products 10x faster than the existing physical trial-and-error process.

Turing Labs is a Series A funded company backed by Insight Partners, Y-combinator, Moment Ventures, and several industry leaders.

The Turing team has decades worth of experience and passion for creating the next generation of products. Today, we employ some of the world’s best machine learning algorithms – and the people who create them – to help drive product innovation that impacts billions of people’s lives.

You can learn more about our journey and where we are going on TechCrunch, VentureBeat, The Wall Street Journal, Business Insider, and Forbes.

Join one of the fastest-growing SaaS on the path of becoming the default platform for product development.

What if the real frontier isn't another chatbot, but an AI that can taste?

We're Turing Labs. The invisible force on path to drive 50,000+ CPG products like the next cereal or sauce or lotion you would use. We've been quietly reformulating what America eats. Now we're building the AI that will revolutionize HOW the $2 trillion CPG industry thinks.

The Foundation Model Nobody Sees Coming

While OpenAI and Anthropic fight over benchmarks, we're building something different.

Your Mission: Architect the Intelligence

As our Foundation Model Research Intern, you won't be fine-tuning models. You'll be generating unique dataset, never sourced before.

Your Daily Reality:

• Morning: Work closely with our AI engineers to design strategies to generate specific segment of data
• Afternoon: Build evaluation frameworks
• Fine-tune specific models with context engineering
• Late afternoon: Present your architecture to our CTO and argue why your approach beats transformers
• Evening: Watch your model predict specific scenario

The Technical Challenge:

• Design knowledge distillation pipelines from expert interviews → structured data → model weights
• Create evaluation metrics for subjective experiences (how do you benchmark "deliciousness"?)
• Develop few-shot learning approaches using our proprietary knowledge base

You'll Have Access To:

• Compute resources that would make your university lab jealous
• Direct mentorship from our technical team
• CEO and top minds in AI

We're Looking For:

• The student who implemented papers for fun before the official code dropped
• Someone who thinks "Attention Is All You Need" was just the beginning
• Equal comfort with PyTorch, LLMS, fine-tuning, evaluation framework, and context engineering
• The kind of person who's built at least one model that made their professor say "wait, how?"
• Bonus: You've thought about AGI while eating lunch and wondered if intelligence can be... tasty?

Why This Internship Hits Different:

• You're not optimizing ad clicks;
• Your model won't write poetry - it'll reformulate products 300 million Americans consume
• Real shot at co-authoring papers that'll make NEURIPS reviewers do a double-take

To Apply, Send Us:

1. GitHub/research portfolio (we'll actually read your code)
2. 300 words or 2-minute video: "How I'd teach an AI to taste"
3. Your wildest idea for using transformer architectures outside NLP/vision
4. One question about our approach that would stump our CTO (we dare you)

P.S. - We can't tell you everything (stealth mode has its rules), but we would be happy to share more details during interview process.

Python, Postgres, Typescript, React or Node.js, and Python.