Annapurna Labs Ltd.
Software Development, Cloud Computing
SeniorMLSoftwareEngineer
Neural analysis suggests this role is
optimal for Senior candidates.
“Senior ML Software Engineer at Annapurna Labs Ltd.. Skills: ML Software Engineering, Inference Data Plane, Custom Hardware. Develop compute kernels. Optimize compute kernels”
Industry & Context.
Root cause analysis; Troubleshooting
What They're Looking For.
Must Have
Bachelor's degree in computer science, 7+ years software development life cycle, Knowledge of Machine Learning and LLM fundamentals, Knowledge of computer architecture, Knowledge of operating systems, Knowledge of parallel computing, Proficiency in C/C++, Linux systems knowledge, Experience developing compute kernels
Nice to Have
Knowledge of ML frameworks, Experience developing and deploying LLMs, Experience with CUDA kernels, Experience with ML/low-level kernels, Familiarity with speculative decoding, Familiarity with KV cache optimization, Familiarity with LLM serving optimizations, Experience with distributed systems, Experience with hardware simulation environments, Experience with model validation workflows, Demonstrated early adopter of AI-assisted development tools
What You'll Do.
Develop compute kernels
Optimize compute kernels
Implement LLM architectures
Validate LLM architectures
Integrate accelerator backends
Build test infrastructure
Maintain test infrastructure
Profile inference workloads
Optimize inference workloads
Instrument critical paths
Drive latency improvements
Drive throughput improvements
Own features end-to-end
Contribute to CI/CD pipelines
Raise engineering bar
How You'll Work.
Team & Collaboration
Cross-functional teams; Design reviews
Process & Methodology
Software development life cycle
Full Job Description
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 engi
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