26 to 50 of 73 vLLM Jobs in the UK

APIs, SDKs, CLIs, notebooks Infrastructure: storage, networking, IAM, observability, infrastructure-as-code Familiarity with tools such as PyTorch, Ray, Slurm, MLflow, Langchain, Hugging Face, vLLM, Triton, or similar. Able to balance performance, cost, usability, flexibility, and reliability. Strong prioritisation, communication, and stakeholder management skills. Comfortable taking ambiguous problems from discovery ...

also be interested to hear about any experience you have in the following areas: Experience with ML frameworks and LLM inference, such as PyTorch, vLLM, SGLang, llama. cpp or similar Experience analysing and optimizing CPU performance in heterogeneous CPU + accelerator systems Familiarity with agentic AI frameworks and protocols Understanding ...

with the open‐weight model landscape and the trade‐offs between regional and multilingual models Experience with an inference serving engine behind the gateway — vLLM, SGLang, or TGI for production serving; Ollama for lightweight on‐prem — and sizing GPU capacity for self‐hosted models (KV‐cache footprint, concurrent batch size ...

engineering & synthetic data pipelines Agentic frameworks, reasoning, tool use, memory systems Evaluation & benchmarking (LLM-as-judge, safety/alignment metrics) Inference optimisation (quantization, distillation, vLLM/TensorRT-LLM) Requirements: - PhD or Master's in CS/AI/ML/Physics/Maths or equivalent research experience - Strong hands ...

design, operational risk and engineering trade-offs. Fluent Python and daily use of coding agents. NICE TO HAVE Inference engines such as SGLang or vLLM, and RL training frameworks such as veRL, Miles or TRL. Agent environment and evaluation frameworks such as Harbor. Sandboxed execution for agents, such as Firecracker ...

training frameworks such as veRL, Miles or TRL, RL environment frameworks such as Harbor or Prime Intellect's verifiers, and inference engines such as vLLM or SGLang. Building agent harnesses and long-horizon tasks with tool use, such as search, code execution and external APIs. Designing learning signals for long ...

with hardware/software co-design, or with hardware performance modelling and simulation. Contributions to performance-critical open-source projects (e.g. PyTorch, Triton, JAX, vLLM). A collaborative and supportive work environment The opportunity to have a high impact in a growing organisation Competitive salary package and pension Professional development ...

stand out from the crowd: Experience with Nemotron, DeepSeek, Qwen, Mistral, MiniMax, GLM, Kimi, NeMo, NIM, NVIDIA Agent Toolkit, Dynamo, TensorRT-LLM, Triton, vLLM, SGLang, Hugging Face, or similar ecosystems. Experience turning agentic AI, open models, secure AI deployment, or regulated AI requirements into field playbooks, workshops, demos, and executive ...

with distributed computing frameworks (e.g., Ray, Spark), or specialised batch schedulers/resource managers (e.g., Slurm, Volcano, Kueue). Demonstratedexpertisewith specialised serving engines (e.g.,vLLM,SGLang) or techniques for deploying models in resource-constrained or high-throughput environments. Familiarity withGitOpsand CI/CD (e.g.,ArgoCD,GitHubActions). Experience managing ...

platform, or AI infrastructure product. Knowledge of GPU inference and model‐serving technologies , including batching, quantization, KV caching, capacity planning, and frameworks such as vLLM, SGLang, or TensorRT‐LLM. Experience with LLM evaluation, benchmarking, and production applications , such as AI agents, coding assistants, and retrieval‐augmented generation systems. Experience with ...

management in development tools and software including CLIs, SDKs and APIs. Knowledge of machine learning frameworks, runtimes, infrastructure such as PyTorch, ONNX, ExecuTorch, Llama.cpp, vLLM and LiteRT. Understanding of model deployment to edge, embedded or heterogeneous computing, with an understanding of trade-offs between accuracy, performance and power consumption. ...

also be interested to hear about any experience you have in the following areas: Experience with ML frameworks and LLM inference , such as PyTorch, vLLM, SGLang, llama.cpp or similar Experience analysing and optimizing CPU performance in heterogeneous CPU + accelerator systems Familiarity with agentic AI frameworks and protocols Understanding ...

engineering experience, ideally with hands‐on work in inference optimization, model training, GPU programming, or ML infrastructure You’re familiar with the serving (e.g., vLLM, SGLang) and training (e.g., slime, verl, TRL) toolchains and can go deep on at least one (you don’t need all of them ...

Skills and Experience : Experience using software simulators and/or FPGAs Exposure to any of the following: driver development, inference engines like llama.cpp or vLLM, performance analysis of ML and GenAI workloads, knowledge of Neural Network Processing Units (NPU) or Graphics Processing Units (GPU) and how they are used ...

throughput-optimized setups. Driving consistent “playbook” style deployments for common models and use cases. Become a power user of different runtimes such as vLLM, SGLang, and TRT-LLM and all the common configurations and tradeoffs between them Drive POC and project execution , including: Scoping POCs and keeping stakeholders aligned ...

other image-intelligence work.* Text recognition in low-quality images and video, including non-Latin scripts.* Serving open-weight models efficiently in production, with vLLM or similar.* Distributed training across multiple GPUs.## What you'll getWe're a small, performance-driven team at one of the fast-growing startups ...

upgrades, node drain states, and control plane troubleshooting. Familiarity with the inference and training stack that ML platform teams build on, such as vLLM, SGLang, TensorRT-LLM, or NCCL, and with how benchmarks such as MLPerf are run and reported. Experience writing for both the platform engineers who operate ...

post-training Experience with distributed training and GPU systems Strong experimental judgement Ability to work comfortably across ML research and systems engineering Optional vLLM, SGLang, Ray, FSDP or Megatron-LM CUDA, Triton, CuTE or GPU performance optimisation Shortlisted candidates will be contacted within 48 hours. #J-18808-Ljbffr ...

commonly used databases such as PostgreSQL, Clickhouse, and MongoDB PREFERRED SKILLS AND EXPERIENCE: Experience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM) Experience designing or building with agent SDKs and agent orchestration frameworks Experience with Docker, Kubernetes, and containerized applications Expert knowledge of gRPC (unary, response streaming ...

transformer inference, including prefill versus decode, KV‐cache behaviour, attention variants and performance bottlenecks Hands‐on experience with LLM serving frameworks such as vLLM, SGLang, TensorRT‐LLM or TGI, and the PyTorch ecosystem Experience with inference optimisation techniques, including quantisation, speculative decoding and model parallelism across modern GPU architectures Strong ...

GDPR. Experience with self-hosted LLM/RAG systems, GPU infrastructure, or AI model-serving technologies such as vLLM or TGI. Familiarity with enterprise infrastructure and security technologies such as RHEL/OpenShift, VMware, Windows/AD, PKI, RBAC/ABAC, and SIEM integrations. Experience with threat intelligence sharing standards ...

accelerator infrastructure across vendors and generations, and a practical understanding of AI training and inference workloads. Experience with inference serving at scale (e.g. vLLM, SGLang, TensorRT‐LLM, batching and scheduling) and with GPU‐sharing techniques (e.g. MIG, MPS, time‐slicing). A 0‐to‐1 track record: comfortable being hands ...

field. Strong knowledge of distributed systems, operating systems,machine learning systems architecture, Inference serving, and AI Infrastructure. Hands-on experience withLLM serving frameworks(e.g.,vLLM,Ray Serve,TensorRT-LLM,TGI) anddistributed KV cache optimization. Proficiency inC/C++, with additional experience inPythonfor research prototyping. Solid grounding insystems research methodology,distributed ...

such as PostgreSQL, Clickhouse, and MongoDB Knowledge of service observability and reliability best practicesExperience with LLM inference engines and serving frameworks (e.g., SGLang, TensorRT, vLLM) Experience designing or building with agent SDKs and agent orchestration frameworks Experience with Docker, Kubernetes, and containerized applications Expert knowledge of gRPC (unary, response streaming ...

throughput and cost per token, partnering with the CUDA/GPU engineers Make the core software architecture calls on serving frameworks and orchestration (e.g. vLLM, TensorRT-LLM, SGLang, Triton Inference Server or equivalents) Translate throughput, latency and uptime commitments into concrete technical specifications and serving capacity plans Act as direct ...