ML Runtime and Kernel Engineer - Core ML - Sunnyvale, CA, United States
Originally posted 28 September 2026 by the employer.
About the role
This role involves developing novel machine learning algorithms that leverage the Cerebras Wafer-Scale Engine, bridging research ideas with efficient execution on Cerebras systems.
What you'll do
- Design and implement runtime components and high-performance kernels required by novel Core ML algorithms. - Translate research prototypes into efficient implementations for the Cerebras platform. - Profile and debug performance across the ML framework, compiler, runtime, communication, and kernel layers. - Optimize computation, memory movement, communication, and concurrency for large-scale training and low-latency inference. - Develop benchmarks, instrumentation, and automated tests that validate functionality, performance, and numerical correctness. - Collaborate with Core ML researchers and compiler, runtime, kernel, and inference engineers to deliver end-to-end capabilities.
What you'll need
- Experience developing high-performance systems software, ML systems, runtimes, compilers, or computational kernels. - Strong programming skills in C++ and Python. - Solid understanding of parallel programming, memory management, concurrency, data structures, and performance optimization. - Proven ability to debug and profile complex software across multiple layers of a system. - Familiarity with modern machine learning architectures and frameworks such as PyTorch or JAX. - Ability to work effectively with researchers and translate evolving algorithmic requirements into reliable software.
Nice to have
- Experience with CUDA, Triton, low-level assembly, accelerator programming, or a C-like domain-specific language. - Experience with compiler internals, distributed runtimes, custom hardware interfaces, or HPC systems. - Understanding of machine learning fundamentals and ML systems, with the ability to reason about how algorithmic choices affect accuracy, systems implementation and performance. - Familiarity with LLM training or inference, including attention, KV-cache management, parallel generation, or distributed execution. - Experience developing software in an industrial or academic research environment where requirements evolve through experimentation. - Contributions to significant open-source systems, ML frameworks, compilers, or kernel libraries.
This role has been open 12 days — well below the 59-day median for Systems Software Engineering roles.
Systems Software Engineering · Systems Software
|
Open roles in category
683
|
Median days open
59 d
|
Median salary
$213k
|
See the full market breakdown ▾Category comparison, and who else is hiring
| Metric | Cerebras | All employers we track in this specialty (683 roles · 73 employers) |
|---|---|---|
| Open roles in this specialty | 13 | 683 |
| Open roles in the wider Software, Firmware & Systems family | 77 | 6035 · 146 employers |
| Median days open | 76 d | 59 d (+17 d vs this employer) |
| Median salary (USD postings) | — | $213k |
Who's hiring in this category
- Qualcomm · 169 open roles · median 74 d
- NVIDIA · 128 open roles · median 51 d
- AMD · 59 open roles · median 50 d
- Mobileye · 29 open roles · median 73 d
- Broadcom · 22 open roles · median 45 d
- Arm Holdings · 20 open roles · median 107 d
How we counted: 683 open Systems Software Engineering (Systems Software) roles from 73 employers tracked in the SemiconductorJobs index, counted 10 Oct 2026. Specialty figures count only roles carrying this exact specialty label, so an employer's related work in neighbouring specialties is not included there — it is counted in the wider Software, Firmware & Systems family row. Figures refresh nightly.