ML Software Engineer, Data Plane

Description

The MLIL DataPlane team is looking for a 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 an individual contributor 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 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.

Basic Qualifications

• Bachelor's degree or equivalent

• 4+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

• 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

Preferred Qualifications

• Knowledge of ML frameworks including JAX, PyTorch, vLLM, SGLang, Dynamo, TorchXLA, and TensorRT

• Knowledge of Machine Learning and LLM fundamentals, including transformer architecture, training/inference lifecycles, and optimization techniques

• Experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware

• Familiarity with speculative decoding, KV cache optimization, or other LLM serving optimizations

• Experience with distributed systems - collective communication, RDMA, or high-speed interconnect programming

• Demonstrated early adopter of AI-assisted development tools - uses LLMs or code-generation agents as part of daily workflow

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Company - Annapurna Labs Ltd.

Job ID: A10495487