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.
A systems-level engineer specializing in build infrastructure and low-level systems optimization, with expertise in maintaining and improving non-trivial C/C++ builds and other host level systems. This role requires deep technical knowledge of compilation processes, hardware-software interfaces, build systems, and the ability to debug and optimize at the system level.
Responsibilities:Build Systems & Toolchains
- Expert-level proficiency with build/packaging systems (Nix, pip, uv, CMake, Bazel, Make, etc…)
- Nix experience in particular is a huge plus
- Experience managing complex builds and interacting in non-trivial ways with CI
- Skilled in diagnosing and resolving linking issues, symbol resolution problems, and toolchain/ABI incompatibilities
Low-Level Systems/Embedded Programming
- Strong C/C++ debugging skills, especially nice if in embedded systems or in dealing with cross compiling/linking
- Comfortable with system calls, POSIX APIs, and kernel interfaces
- Experience with toolchain debugging tools like readelf, bloaty, c++filt, nm, etc…
Compiler & Toolchain Experience
- Basic knowledge of compilers (understanding things like passes, having multiples levels of IR, what kinds of operations are done on it, etc…)
- Experience with cross-compilers (compiling code for target devices)
- Experience with detailed compiler flags optimization and custom toolchain configuration
- Understanding of linking processes, object file formats (ELF, DWARF), and ABI compatibility
Machine Learning Infrastructure
- Basic understanding of deep learning frameworks (PyTorch, Jax) from a systems perspective
- Understanding of tensor operations
- Experience with distributed training infrastructure is a plus
- 5+ years of experience in systems programming or infrastructure roles
- Often comes from backgrounds in: HPC, game engine development, embedded systems, OS, or compiler teams
- Strong debugging mindset with patience for complex, multi-layered issues
- Self-directed problem solver who can navigate large, legacy codebases
This profile would be ideal for roles in ML infrastructure teams, HPC environments, or any organization dealing with non-trivial C/C++ systems that need optimization at the build and runtime level.
Deadline to apply: None. Applications will be reviewed on a rolling basis.
The expected base compensation for this position is below. Our total compensation package for full-time employees includes equity, benefits, and may include incentive compensation.
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.
How we're differentWe 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
Top Skills
What We Do
Anthropic is an AI safety and research company that’s working to build reliable, interpretable, and steerable AI systems. Our research interests span multiple areas including natural language, human feedback, scaling laws, reinforcement learning, code generation, and interpretability.
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