AI/ML Distributed Systems Engineer

October 19

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Interop Labs

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blockchain • cryptography • interoperability • web3

11 - 50

Description

• Design and build efficient compute environments for AI/ML workloads on the intersection of distributed systems/blockchain technologies. • Build and extend AI compute engines to achieve cutting edge performance for specific workload footprints. • Evaluate models and workloads on different hardware and software stacks. • Collaborate with cross-functional teams to design, implement, and optimize the AI engines.

Requirements

• BSc, MSc or Ph.D. specializing in distributed systems and AI. • Excellence in Python, Rust, and/or Go programming languages. • Expertise in building and leveraging large-scale AI systems for training and inference such as Hugging Face, vLLM, CUDA. • In-depth understanding of performance and system bottlenecks in AI applications. • Knowledge of the performance characteristics of AI workloads and optimization strategies.

Benefits

• Unlimited time off throughout the year to rest and recharge. • Competitive compensation with stock options, experiencing growth from the initial phase.