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.

Anthropic is seeking a Linux OS and System Programming Subject Matter Expert to join our Infrastructure team. In this role, you'll work on accelerating and optimizing our virtualization and VM workloads that power our AI infrastructure. Your expertise in low-level system programming, kernel optimization, and virtualization technologies will be crucial in ensuring Anthropic can scale our compute infrastructure efficiently and reliably for training and serving frontier AI models.

Responsibilities:

• Optimize our virtualization stack, improving performance, reliability, and efficiency of our VM environments

• Design and implement kernel modules, drivers, and system-level components to enhance our compute infrastructure

• Investigate and resolve performance bottlenecks in virtualized environments

• Collaborate with cloud engineering teams to optimize interactions between our workloads and underlying hardware

• Develop tooling for monitoring and improving virtualization performance

• Work with our ML engineers to understand their computational needs and optimize our systems accordingly

• Contribute to the design and implementation of our next-generation compute infrastructure

• Share knowledge with team members on low-level systems programming and Linux kernel internals

• Partner with cloud providers to influence hardware and platform features for AI workloads

You may be a good fit if you:

• Have experience with Linux kernel development, system programming, or related low-level software engineering

• Understand virtualization technologies (KVM, Xen, QEMU, etc.) and their performance characteristics

• Have experience optimizing system performance for compute-intensive workloads

• Are familiar with modern CPU architectures and memory systems

• Have strong C/C++ programming skills and ideally experience with systems languages like Rust

• Understand Linux resource management, scheduling, and memory management

• Have experience profiling and debugging system-level performance issues

• Are comfortable diving into unfamiliar codebases and technical domains

• Are results-oriented, with a bias towards practical solutions and measurable impact

• Care about the societal impacts of AI and are passionate about building safe, reliable systems

Strong candidates may also have experience with:

• GPU virtualization and acceleration technologies

• Cloud infrastructure at scale (AWS, GCP)

• Container technologies and their underlying implementation (Docker, containerd, runc, OCI)

• eBPF programming and kernel tracing tools

• OS-level security hardening and isolation techniques

• Developing custom scheduling algorithms for specialized workloads

• Performance optimization for ML/AI specific workloads

• Network stack optimization and high-performance networking

• Experience with TPUs, custom ASICs, or other ML accelerators

Representative projects:

• Optimizing kernel parameters and VM configurations to reduce inference latency for large language models

• Implementing custom memory management schemes for large-scale distributed training

• Developing specialized I/O schedulers to prioritize ML workloads

• Creating lightweight virtualization solutions tailored for AI inference

• Building monitoring and instrumentation tools to identify system-level bottlenecks

• Enhancing communication between VMs for distributed training workloads

Deadline to apply: None. Applications will be reviewed on a rolling basis.

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.

Annual Salary:
$300,000—$405,000 USD

Logistics Education requirements:

We require at least a Bachelor's 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 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