Thinking Machines Talent Exodus Continues as AI Hiring War Intensifies

The AI talent war is accelerating and again Thinking Machines Lab is at its center.

According to MSN: Joshua Gross, a founding team member at the startup, has rejoined Meta Platforms, where he will lead engineering efforts within its Superintelligence Labs. Gross had previously worked at both Meta and OpenAI before joining Thinking Machines in early 2025.

His departure is the latest in a series of high-profile exits. Meta has reportedly hired multiple founding members from the company, including co-founder Andrew Tulloch, while OpenAI has also pulled senior talent back into its ranks.

The backdrop is a rapidly escalating competition for AI expertise. Reports suggest that compensation packages across the industry have reached unprecedented levels, with signing bonuses, equity grants, and retention incentives now measured in the tens, and sometimes hundreds, of millions.

Thinking Machines itself has been actively recruiting, bringing in high-profile hires such as Soumith Chintala as CTO and expanding to roughly 130 employees within a year of launch. The company raised $2 billion at a $12 billion valuation, positioning itself as one of the most prominent “unicorn-at-birth” AI startups.

But the same dynamic that enabled its rapid rise is now being tested.

TheMarketAI Take

We’ve covered this phneomen: some of the newest AI startups are being valued primarily on talent concentration rather than shipped product. That model works great for an NBA team until the talent moves.

Thinking Machines is becoming a real-time case study. With multiple founding members and senior engineers departing before a product has fully matured, the underlying question becomes unavoidable:

If the asset is the people, what happens to the valuation when the people leave?

In traditional startups, value compounds through products, customers, and revenue. In many AI-native startups, value is still being formed — and in some cases, priced ahead of execution.

At the same time, incumbents like Meta and OpenAI have structural advantages.

They offer not just compensation, but scale, infrastructure, and the ability to deploy talent immediately against massive compute and data resources.

This creates a new dynamic in venture-backed AI:

• Talent forms quickly

• Capital follows instantly

• But retention becomes the real battleground

The result is a more fluid, and potentially more fragile, startup model.

Thinking Machines may still succeed — it continues to attract top-tier hires and capital. But the broader lesson is emerging clearly:

In the AI era, talent is both the moat and the risk.

Here's Thinking Machines Labs original founding team: (source: https://thinkingmachines.ai).

Name	Bio
Alex Gartrell	Former Leader of Server Operating Systems at Meta, expert in Linux kernel, networking, and containerization.
Alexander Kirillov	Co-creator of Advanced Voice Mode at OpenAI and Segment Anything Model (SAM) at Meta AI, previously multimodal post-training lead at OpenAI.
Andrew Gu	Previously working on PyTorch and Llama pretraining efficiency.
Andrew Tulloch (Chief Architect)	ML systems research and engineering, previously at OpenAI and Meta.Moved back to Meta October 2025
Barret Zoph (CTO)	Formerly VP of Research (post-training) at OpenAI. Co-creator of ChatGPT.
Brydon Eastman	Formerly post-training research at OpenAI, specializing in human and synthetic data, model alignment and RL.
Chih-Kuan Yeh	Previously Building data for Google Gemini and Mistral AI.
Christian Gibson	Formerly infrastructure engineer at OpenAI, focused on supercomputers used in training frontier models.
Devendra Chaplot	Founding team member & Head of Multimodal Research at Mistral AI, co-creator of Mixtral and Pixtral. Expert in VLMs, RL, & Robotics.
Horace He	Interested in making both researchers and GPUs happy, formerly working on PyTorch Compilers at Meta, co-creator of FlexAttention/gpt-fast/torch.compile
Ian O'Connell	Infrastructure engineering, previously OpenAI, Netflix, Stripe.
Jacob Menick	ML researcher, led GPT-4o-mini at OpenAI, previously contributed to the creation of ChatGPT and deep generative models at DeepMind.
Joel Parish	Security generalist, helped ship and scale the first versions of ChatGPT at OpenAI.
John Schulman (Chief Scientist)	Pioneer of deep reinforcement learning and creator of PPO, cofounder of OpenAI, co-led ChatGPT and OpenAI post-training team.
Jonathan Lachman	Operations executive, former head of special projects at OpenAI and White House national security budget director.
Joshua Gross	Built product and research infrastructure at OpenAI, shaping ChatGPT's learning systems and GPU fleet; previously on product infra at Meta. Moved back to Meta April 2026
Kevin Button	Security engineer focused on infrastructure and data security, formerly at OpenAI.
Kurt Shuster	Reasoning at Google DeepMind, full-stack pre-training and inference at Character.AI, and fundamental dialogue research at Meta AI.
Kyle Luther	ML researcher, previously at OpenAI.
Lia Guy	Previously at OpenAI and DeepMind, working on model architecture research.
Lilian Weng	Formerly VP of Research (safety) at OpenAI. Author of Lil'Log.
Luke Carlson	Former ML Engineer in Apple's Machine Learning Research group, designed ML frameworks for model orchestration, speech generation, private federated learning, and image diffusion.
Luke Metz	Research scientist and engineer, previously at OpenAI and Google Brain. Co-creator of ChatGPT.
Mario Saltarelli	Former IT and Security leader at OpenAI.
Mark Jen	Generalist, most recently infra @ Meta.
Mianna Chen	Previously at OpenAI and Google DeepMind. Led advanced voice mode, 4o, 4o-mini, o1-preview, and o1-mini launches.
Mira Murati (CEO)	Former CTO of OpenAI, led OpenAI's research, product and safety.
Myle Ott	AI researcher, founding team at Character.AI, early LLM lead at Meta, creator of FSDP and fairseq.
Naman Goyal	Previously distributed training and scaling at FAIR and GenAI @Meta, most recently LLAMA pretraining.
Nikki Sommer	Formerly VP HRBP at OpenAI and Director, HRBP at Twitter.
Noah Shpak	ML Engineer, loves making data go vroom while GPUs go Brrr.
Pia Santos	Executive Operations Leader, previously at OpenAI.
Randall Lin	Previously babysitting ChatGPT at OpenAI and co-tech leading 'the Twitter algorithm' at X.
Rowan Zellers	Formerly at OpenAI, working on realtime multimodal posttraining.
Ruiqi Zhong	Passionate about human+AI collaboration, previously PhD at UC Berkeley, working on scalable oversight and explainability.
Sam Schoenholz	Led the reliable scaling team and GPT-4o optimization at OpenAI. Previously worked at the intersection between Statistical Physics & ML at Google Brain.
Sam Shleifer	Research engineer specializing in inference, previously at Character.AI, Google DeepMind, FAIR, HuggingFace.
Saurabh Garg	Researcher, formerly working on all things multimodal at Mistral AI. Deep into the magic of pretraining data and loving every byte of it!
Shaojie Bai	Avid ML researcher to make audio-visual models better and faster, previously at Meta.
Stephen Roller	Previously full-stack pre-training at DeepMind, CharacterAI, and MetaAI.
Yifu Wang	Passionate about novel ways of overlapping/fusing GPU compute and communication. Formerly PyTorch @ Meta.
Yinghai Lu	ML system engineer, formerly led various inference efforts at OpenAI and Meta.