12 of 12 vLLM Jobs in the North of England

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...

open-source frontier models Fine-tune models using state-of-the-art methods (LoRA/QLoRA, SFT, DPO, distillation) Architect scalable inference systems using vLLM/TensorRT-LLM/DeepSpeed Build data systems for high-quality synthetic and real-world training data Develop alignment, safety, and guardrail strategies Design evaluation … memory efficiency, quantization, mixed precision Comfortable owning ambiguous, zero-to-one technical problems end-to-end Nice to Have Experience with LLM inference frameworks (vLLM, TensorRT-LLM, FasterTransformer) Contributions to open-source ML libraries Background in scientific computing, compilers, or GPU kernels Experience with RLHF pipelines (PPO, DPO, ORPO) Experience ...