Engineering Manager, Accelerator Platform

About Anthropic

Anthropics mission is to create reliable interpretable and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers engineers policy experts and business leaders working together to build beneficial AI systems.

About the Role

Every time someone talks to Claude -- through the API our cloud partners or any of our expanding surfaces -- the request lands on an AI accelerator. Not one kind many kinds: TPUs Trainium chips GPUs. Each arrives with its own software stack performance characteristics failure modes and operational quirks. Someone has to take raw silicon and turn it into a platform that the rest of Anthropic can build on without thinking about which chip is underneath. Thats us.

The Accelerator Platform team owns the bringup and normalization of new hardware platforms for Anthropics first party inference fleet. We sit between the low-level systems teams and the serving infrastructure that runs production inference -- bridging the gap so that every new accelerator generation ships as a first-class production platform. Its deeply technical work at the intersection of hardware enablement distributed systems and ML infrastructure and it is directly on the critical path for Anthropics compute strategy.

Were hiring an Engineering Manager to build and lead this team. Youll inherit a small nucleus of experienced engineers and grow it into a standalone platform organization. Youll set technical direction hire a strong team and partner closely with hardware vendors cloud providers and teams across Inference to bring new accelerator generations online quickly and reliably.

Responsibilities:

• Build and lead the Accelerator Platform team -- hiring developing and retaining engineers who thrive at the hardware/software boundary
• Own the end-to-end bring-up lifecycle for new accelerator platforms (multiple generations of Trainium TPUs and GPUs) from initial silicon availability through production-ready inference
• Define and drive the platform normalization layer -- ensuring new hardware integrates cleanly with Anthropics inference serving stack to provide a consistent abstractio
• Partner with cloud providers (AWS GCP Microsoft Azure) and chip vendors on hardware roadmaps capacity planning and platform-specific technical challenges
• Collaborate closely with teams across Inference and Infrastructure to ensure new platforms meet production reliability and latency requirements from day one
• Contribute to Anthropics multi-cloud compute strategy -- helping the organization maintain optionality across accelerator families and avoid lock-in to any single vendor
• Manage the teams priorities across competing demands: new platform bring-up ongoing production support for existing platforms and longer-term investments in tooling and automation.

You may be a good fit if you:

• Have significant experience managing infrastructure or platform engineering teams (3 years in engineering management)
• Have deep technical fluency in systems programming distributed systems or hardware/software co-design -- you need to understand the stack deeply enough to make sound technical and hiring decisions
• Have experience bringing up or operating heterogeneous compute infrastructure at scale -- whether thats GPU clusters TPU pods custom ASICs or FPGA deployments.
• Are comfortable with ambiguity and can build structure where none exists. This team is being carved out as a new entity; youll be defining its charter processes and culture from scratch
• Think strategically about hardware roadmaps and can translate vendor capabilities into engineering plans
• Build strong cross-functional relationships -- this role requires tight collaboration with hardware vendors cloud partners and half a dozen internal teams
• Care deeply about both technical excellence and the people doing the work.

Strong candidates may also:

• Have direct experience with ML accelerator architectures (GPU/CUDA TPU/XLA Trainium/Neuron or similar)
• Have worked on ML inference serving infrastructure at scale (1000 accelerators)
• Have experience with Kubernetes-based ML workload orchestration
• Understand ML-specific networking (RDMA InfiniBand NVLink ICI) and how interconnect topology affects serving performance
• Have experience managing vendor relationships and influencing hardware/software roadmaps
• Have led teams through rapid growth phases (hiring 5 engineers in a short timeframe).

Logistics

Education requirements: We require at least a Bachelors degree in a related field or equivalent experience.

Location-based hybrid policy: Currently we expect all staff to be in one of our offices at least 25% of the time. However some roles may require more time in our offices.

Visa sponsorship:We do sponsor visas! However we arent able to successfully sponsor visas for every role and every candidate. But if we make you an offer we will make every reasonable effort to get you a visa and we retain an immigration lawyer to help with this.

We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy so we urge you not to exclude yourself prematurely and to submit an application if youre interested in this work. We think AI systems like the ones were building have enormous social and ethical implications. We think this makes representation even more important and we strive to include a range of diverse perspectives on our team.

Your safety matters to us. To protect yourself from potential scams remember that Anthropic recruiters only contact you some cases we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money fees or banking information before your first day. If youre ever unsure about a communication dont click any linksvisit for confirmed position openings.

How were different

We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact advancing our long-term goals of steerable trustworthy AI rather than work on smaller and more specific puzzles. We view AI research as an empirical science which has as much in common with physics and biology as with traditional efforts in computer science. Were an extremely collaborative group and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such we greatly value communication skills.

The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic including: GPT-3 Circuit-Based Interpretability Multimodal Neurons Scaling Laws AI & Compute Concrete Problems in AI Safety and Learning from Human Preferences.

Come work with us!

Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits optional equity donation matching generous vacation and parental leave flexible working hours and a lovely office space in which to collaborate with colleagues. Guidance on Candidates AI Usage:Learn aboutour policyfor using AI in our application process