Senior Software Engineer (ML), Data Plane

The MLIL DataPlane team is looking for a Senior Software Development Engineer to own the design and implementation of our inference data plane. We build the software that makes large models run efficiently on custom hardware - spanning model execution memory management data movement and serving integration.
Our work covers the full inference path: integrating serving engines with custom hardware developing high-performance compute kernels enabling efficient data movement and driving models from early validation through production. We operate at frontier scale with large distributed models.
This is a ground-up effort with rapidly evolving hardware and software. We need a senior IC who can write and optimize low-level code for custom hardware validate model architectures end-to-end build test and profiling infrastructure and drive performance across the stack.

Key job responsibilities
- Develop and optimize compute kernels for a custom ML accelerator architecture targeting production-level performance for large language model inference.
- Implement and validate LLM architectures (decoder-only mixture-of-experts) end-to-end - from PyTorch model definition through distributed execution on custom hardware.
- Integrate custom accelerator backends into open-source ML serving frameworks (vLLM PyTorch) including scheduler extensions memory management and model parallelism.
- Build and maintain test infrastructure for model correctness validation across CPU GPU simulator and hardware targets.
- Profile and optimize inference workloads - identify bottlenecks instrument critical paths and drive latency and throughput improvements from simulation through hardware bringup.
- Own features end-to-end: from design through implementation testing and integration into the broader software stack.
- Contribute to CI/CD pipelines that gate model and kernel changes on correctness and performance regressions.
- Mentor engineers drive design reviews and raise the engineering bar across the team.

- Bachelors degree in computer science or equivalent
- 7 years of full software development life cycle including coding standards code reviews source control management build processes testing and operations experience
- Knowledge of Machine Learning and LLM fundamentals including transformer architecture training/inference lifecycles and optimization techniques
- Knowledge of computer architecture operating systems and parallel computing
- Strong proficiency in C/C
- Strong Linux systems knowledge
- Experience developing compute kernels for GPUs DSPs or custom accelerators
- Proven track record of owning and delivering complex software features end-to-end

- Knowledge of ML frameworks including JAX PyTorch vLLM SGLang Dynamo TorchXLA and TensorRT
- Experience in developing and deploying LLMs in production on GPUs Neuron TPU or other AI acceleration hardware or experience with CUDA kernels or ML/low-level kernels
- Familiarity with speculative decoding KV cache optimization or other LLM serving optimizations
- Experience with distributed systems - collective communication RDMA or high-speed interconnect programming
- Experience with hardware simulation environments and model validation workflows
- Demonstrated early adopter of AI-assisted development tools - uses LLMs or code-generation agents as part of daily workflow

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