Join Anthropic as a Performance Engineer to optimize the inference engine for AI systems at scale.
Posted by employer 2 days ago
First seen on Joblaze 1 day ago
Last verified on the company career page 16 hours ago
Skills & Technologies
What you'll build
- Build and optimize the inference engine
- Improve throughput, cost, reliability, and latency
- Manage memory for weights and activations
- Coordinate forward passes
- Ensure model quality and safety
Must have
- Strong systems programming (Rust, C++, or similar)
- Analytical about performance
- A working mental model of LLM inference
- Proven quick learner
Nice to have
- Experience inside an LLM serving engine
- GPU/Accelerator programming
- OS internals
- Language modeling with transformers
- Experience building an allocator, cache, scheduler
Practical constraints
- Expected to be in the office at least 25% of the time
Requirements
- Education
- Bachelor's degree
- Visa
- Sponsorship available
Not disclosed in this posting: years of experience.
Benefits
Joblaze summary
In this role, the Performance Engineer for the Inference Engine at Anthropic focuses on optimizing the software that manages the token path between accelerator kernels and the routing layer, ensuring high throughput and low latency. Key skills include strong systems programming in languages like Rust or C++, along with a deep understanding of large language model inference and hardware performance metrics. This position is ideal for experienced engineers who thrive in complex, high-performance environments and are comfortable collaborating closely with cross-functional teams. Anthropic emphasizes a cohesive team approach, valuing communication and collaboration in their mission to develop re
Joblaze insights
- Listed yesterday on Joblaze — tracked directly from Anthropic's career page.
- Anthropic has 630 other open roles including External Affairs, South Korea, Reseller Partner Manager, Social Escalations Program Manager .
- 1661 active C++ roles on Joblaze right now.
- 768 active Rust roles on Joblaze right now.
- 127 active GPU roles on Joblaze right now.
- Salary band is above the typical range for AI/ML roles (median ~$188,000).
- Pays more than 99% of the 808 salaried C++ roles we track (median $150,000). See C++ salary trends
Quick facts
- Is the Performance Engineer, Inference Engine role remote?
- It's hybrid — Anthropic expects some on-site time in San Francisco, CA | New York City, NY.
- What's the salary range?
- Anthropic lists $350,000–$850,000 for this role.
- Where is the role based?
- Anthropic is hiring for this position in San Francisco, CA | New York City, NY.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Accelerator programming, C++, GPU, Rust, Transformer Architecture.
- Does Anthropic sponsor work visas for this role?
- Yes — the posting indicates visa sponsorship is available for the right candidate.
- What seniority level is this role?
- Anthropic targets mid-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Performance Engineer, Inference Engine role at Anthropic.
From the original posting
About Anthropic
Anthropic’s 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.
Performance Engineer, Inference Engine
About the Role
Anthropic's inference engine is the software between the accelerator kernels and the routing layer. It manages the entire token path in between: batching requests, laying the model out across chips, managing memory for weights and activations, coordinating every forward pass, and managing model state across requests. Built in-house, it runs on all of our accelerator platforms, serving Claude to millions of users and running our research workloads.
You will work on building and optimizing this system at Anthropic scale: improving throughput, cost, reliability, and latency across all accelerator and cloud platforms. You are intimately familiar with the hardware and bandwidth numbers (FLOPs, HBM, PCIe, RDMA, network links, etc.) and can model a problem quickly: where the time and bytes go, and what sets the bound. The role is deeply technical and high-impact, and suits engineers who enjoy working across accelerator programming, high-performance systems that seamlessly coordinate between host and device, and large-scale distributed systems. Familiarity with the transformer architecture is a plus.
Some example recurring themes:
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Keep device utilization high. Accelerators should never be waiting due to other overheads.
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Reuse instead of recompute. Keep model state cached and reuse it whenever that is cheaper than computing it again.
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Measure, model, then change. We build the observability to see where the gaps are, model the impact of potential improvements, deploy them, and go around again, with Claude speeding up every turn of that loop.
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Tokens you can trust. Ensuring model quality matters more than efficiency. We build the infrastructure to ensure Claude maintains its intelligence across platforms and over time.
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Safety on every token. We work closely with our safeguards and safety teams. The inference engine is the backbone behind our production safety systems, ensuring efficiency without compromising robustness.
Minimum Qualifications
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A working mental model of LLM inference: how prefill and decode land on an accelerator's compute, memory, and interconnect, and what the host is doing meanwhile
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Proven quick learner: ramped fast in deep, unfamiliar systems and shipped consequential changes quickly
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Strong systems programming (Rust, C++, or similar), with care for code quality and tests
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Analytical about performance: observe and profile first, form a hypothesis, test it, then change the code and measure again
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Low ego: ask the naive question, take feedback well, pick up slack outside your job description
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Enjoy pair programming (we love to pair!) and care about the societal impacts of your work
Preferred Qualifications
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Experience inside an LLM serving engine and a sense of where its abstractions strain
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GPU/Accelerator programming
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OS internals
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Language modeling with transformers
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Experience building an allocator, cache, scheduler, or high-bandwidth transport
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Fluency in Rust
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Experience making systems reproducible: determinism, replay, property-based tests
The annual compensation range for this role is listed below.
For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
Logistics
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
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 aren't 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 you're interested in this work. We think AI systems like the ones we're 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 from @anthropic.com email addresses. In 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 you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
How we're 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. We're 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 about our policy for using AI in our application process.