451 to 475 of 801 PyTorch Jobs in England

4+ years' experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks, or generative AI. Advanced proficiency in Python and ML frameworks such as PyTorch or TensorFlow . Hands-on experience developing or fine-tuning LLaMA , GPT , or similar foundation models. Understanding of agentic architectures , chain-of-thought reasoning, and memory/reflection mechanisms. Proven More ❯

4+ years’ experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks, or generative AI. Advanced proficiency in Python and ML frameworks such as PyTorch or TensorFlow . Hands-on experience developing or fine-tuning LLaMA , GPT , or similar foundation models. Understanding of agentic architectures , chain-of-thought reasoning, and memory/reflection mechanisms. Proven More ❯

4+ years’ experience in Machine Learning or AI , with exposure to LLM agent systems , tool-use frameworks, or generative AI. Advanced proficiency in Python and ML frameworks such as PyTorch or TensorFlow . Hands-on experience developing or fine-tuning LLaMA , GPT , or similar foundation models. Understanding of agentic architectures , chain-of-thought reasoning, and memory/reflection mechanisms. Proven More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

from concept to code without getting lost in the theory. You've already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you're confident designing APIs, microservices, and data pipelines. Maybe you've come from an academic background and More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic background and More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

using Jira and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/ More ❯

Engineering, Statistics, or a related field. Practical experience in training, fine-tuning, transformer models or LLMs e.g., using text, audio and/or images. Practical Python coding experience leveraging PyTorch or similar framework Excellent analytical, coding, communication, and collaborative skills. Preferred Field of research and publications directly related to multimodal AI, including e.g., computer vision and audio modelling – with an More ❯

for data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯

for data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯

for data curation, versioning, and reproducible experimentation. You'll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯

for data curation, versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO More ❯