Conduct product testing and application evaluations using established laboratory methods. * Knowledge of formulation chemistry, material science, and laboratory testing methods.
Conduct product testing and application evaluations using established laboratory methods. * Knowledge of formulation chemistry, material science, and laboratory testing methods.
Drive test method development incorporating relevant standards requirements such as ISOs and/or Pharmacopeia and relevant AbbVie internal and/or external interfaces (regarding method comparability, applicable specifications, requirements for commercial process for in-process controls and/or release tests). * Validation of test methods for performance testing of Combination Products. * Method Transfers and/or Co-Validation to relevant internal or external interfaces.
Drive test method development incorporating relevant standards requirements such as ISOs and/or Pharmacopeia and relevant AbbVie internal and/or external interfaces (regarding method comparability, applicable specifications, requirements for commercial process for in-process controls and/or release tests). * Validation of test methods for performance testing of Combination Products. * Method Transfers and/or Co-Validation to relevant internal or external interfaces.
You will explore and implement LLM‑based methods and agentic AI approaches to enhance automation, decision support and model interpretability in real retail scenarios.
You will explore and implement LLM‑based methods and agentic AI approaches to enhance automation, decision support and model interpretability in real retail scenarios.
Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding, data/tensor/expert/pipeline-parallelism, prefill-decode disaggregation. * Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories. * Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).
Contribute features to vLLM that empower the newest models with the latest NVIDIA GPU hardware features; profile and optimize the inference framework (vLLM) with methods like speculative decoding, data/tensor/expert/pipeline-parallelism, prefill-decode disaggregation. * Strong programming skills in Python and C/C++; experience with Go or Rust is a plus; solid CS fundamentals: algorithms & data structures, operating systems, computer architecture, parallel programming, distributed systems, deep learning theories. * Familiarity with GPU programming and performance: CUDA, memory hierarchy, streams, NCCL; proficiency with profiling/debug tools (e.g., Nsight Systems/Compute).
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