Software Engineer, Accelerator Build Infrastructure
San Francisco, CA | Seattle, WAFull-TimeMid-levelSoftware Engineering
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.
About the Role
- 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.
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
You may be a good fit if you have:
- 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 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.
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.
