Software Dev Engineer - Compiler, Annapurna Labs
DESCRIPTION
Are you excited about Machine Learning, chip acceleration, compilers, storage, systems or EC2? Are you passionate about delivering high quality services that affect hundreds of thousands of users? We are the dubbed the "secret sauce" behind AWS's success with development centers in the U.S. and Israel, Annarpuna is at the forefront of innovation by combining cloud scale with the world’s most talented engineers.
The Annapurna team hires for multiple disciplines Software and Hardware engineers including but not limited to complier engineer, machine learning engineer, runtime engineer, performance engineer and ML chip accelerator, ASIC, physical designs, SDE in Test. Because of our teams’ breadth of talent, we’ve been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and F1 EC2 Instances, in machine learning with AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe.
Key job responsibilities
Innovating and delivering creative SW Designs to develop new services, solve operational problems, drive improvements in developer velocity, or positively impact operational safety
Writing requirements capturing documents, design documents, integration test plans, and deployment plans
Communicating status and progress of deliverables to schedule, and sharing learnings/ innovations with your team and stakeholders
BASIC QUALIFICATIONS
Currently enrolled in, or completed a Bachelor’s degree program or higher in Computer Science, Computer Engineering, Electrical Engineering or related field
To qualify, applicants should have earned a Bachelor’s or Master’s degree between May 2023 to September 2025. Possible start dates for this role are between January 2025 to October 2025.
Programming experience in internship or coursework with programming language such as Python and/or C or C++.
Candidates with strong interests and academic qualifications/research focus in two of the following:
Knowledge of code generation, compute graph optimization, resource scheduling
Data structure and algorithms
Compiler - Optimizing compilers (internals of LLVM, clang, etc)
Machine Learning - Experience with XLA, TVM, MLIR, LLVM
Deep learning models and algorithms
Tensorflow, PyTorch, or MxNET frameworks
PREFERRED QUALIFICATIONS
Knowledge of code generation, compute graph optimization, resource scheduling
Previous technical internship(s), if applicable.
Experience in optimization mathematics such as linear programming and nonlinear optimization.
Ability to effectively articulate technical challenges and solutions.
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