Workloads Engineer
Tasks
- Analyze LLM architectures and execution requirements
- Contribute to AI execution stack and system architecture decisions
- Deploy and scale AI workloads in production environments
- Design high performance software components for AI frameworks and runtimes
- Identify and remove performance bottlenecks across model runtime and hardware
- Optimize workloads for latency throughput memory efficiency parallel execution accuracy and stability
- Translate AI models into optimized execution workloads
Perks/Benefits
Skills/Tech-stack
C++ | CUDA | Computer Architecture | Distributed Systems | JAX | Language Models | Large Language Models | Numerical analysis | OpenCL | Parallel Computing | Performance Tuning | PyTorch | Python | TensorFlow | Transformers
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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