1 to 25 of 51 Permanent PyTorch Jobs in London

implementation experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

implementation experience NLP and Conversational AI development Model training, testing and evaluation Prompt Engineering and AI workflow optimisation Programming & Frameworks Strong Python development skills PyTorch TensorFlow Scikit-Learn LangChain LangGraph Hugging Face FastAPI REST APIs Data Technologies SQL NoSQL Databases Data Modelling ETL Development Data Pipeline Engineering Vector Databases such ...

experience productionising models and building scalable ML systems. Machine Learning Engineer, key skills: Strong experience in Python (e.g. pandas, scikit-learn, NumPy, TensorFlow/PyTorch) Proven experience in model productionisation and deployment in real-world environments Hands-on experience with MLOps, including CI/CD for ML, versioning, and monitoring ...

problem-solving skills. Preferred Qualifications/Skills Experience with healthcare AI, clinical analytics, or medical data science. Experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. Familiarity with cloud platforms including AWS, Azure, or Google Cloud. Experience with generative AI, large language models (LLMs), and retrieval-augmented ...

async programming, concurrency, multithreading) Expertise in RESTful API design, OpenAPI/Swagger documentation and API lifecycle best practices Hands-on experience with ML libraries: PyTorch, PySpark, scikit-learn, Hugging Face Transformers Proficiency in AI tooling: Azure ML, Databricks, MLflow, LangChain, LangGraph Proven experience with Git, unit testing, containerisation and agile ...

using LangChain and LangGraph (agent architecture design, state management, and graph-based workflow orchestration). ML & Cloud Ecosystems: Solid understanding of ML algorithms, FastAPI, PyTorch/TensorFlow, MLflow, MLOps practices, containerization (Docker, Kubernetes/AWS EKS), and cloud services (AWS Bedrock, SageMaker, Azure AI Search). Soft Skills: Excellent communication ...

strong experience developing and deploying machine learning and generative AI solutions in production environments. * Strong Python engineering skills with experience using frameworks such as PyTorch, TensorFlow, LangChain, or similar. * Experience working with LLMs, prompt engineering, vector databases, and retrieval augmented generation (RAG) architectures. * Strong knowledge of cloud platforms including ...

Track record of leading ML/AI technical initiatives across multiple teams Strong experience with cloud platforms (AWS, Azure, GCP) Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG) Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

native architecturesTrack record of leading ML/AI technical initiatives across multiple teamsStrong experience with cloud platforms (AWS, Azure, GCP)Experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG)Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality ...

LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options ...

Scrum practices and a strong Agile mindset.· Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch)· Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such as vector databases.· Strong expertise ...

. Multimodal Pipelines – Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML Frameworks – Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms like Google Vertex AI or AWS Sagemaker. Education – BS in Computer Science, Engineering, Data Science, or equivalent technical field. ...

related role. Proven experience in designing and deploying generative AI models and solutions. Hands-on experience with AI frameworks and tools such as TensorFlow, PyTorch, Hugging Face, etc. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and deploying AI solutions in cloud environments. Technical Skills: Proficiency in programming languages ...

optimisation Tech environment Key technologies include: Python Azure Databricks Generative AI/LLM frameworks Agentic AI tooling and orchestration frameworks LangChain/LangGraph PyTorch and ML libraries REST APIs Docker and containerisation CI/CD pipelines Git-based development workflows What we're looking for 4-6 years' experience within ...

Foundry, Databricks, AWS (all three ideal) Deep expertise in GenAI, agentic AI, RAG patterns, LLM fine-tuning, and vector databases Strong Python foundations — PyTorch, Transformers, FastAPI, LangChain/LangGraph Experience with MLOps, CI/CD, IaC, and container orchestration at enterprise scale Confident communicator — able to engage CXOs and engineering ...

LLMs, NLP, or computer vision projects Knowledge of AWS, Azure, or GCP Familiarity with Docker, APIs, or Git workflowsFamiliarity with frameworks such as PyTorch, TensorFlow, or Scikit-learn Internship, university project, or personal portfolio related to AI/ML What’s on Offer Competitive graduate salary package Company stock options ...

around cloud architecture, scalability, and system design Help establish engineering best practices in a fast-moving early-stage environment Tech Stack Python TensorFlow/PyTorch LLM frameworks (LangChain, LangGraph, or similar agentic AI tooling) AWS/Azure cloud platforms (including AI services such as Bedrock) Data engineering tools (e.g. ...

databases or the MCP protocol. Deep understanding of LLMs, prompt engineering, model evaluation, and fine‐tuning strategies. Strong proficiency in ML frameworks (e.g., TensorFlow, PyTorch) and cloud platforms (AWS, Azure, GCP). Experience with AI infrastructure components including model gateways, orchestration layers, and observability tools. Familiarity with AI governance, data ...

OpenAI, Anthropic, Llama), prompt engineering, fine‐tuning/customization, and embedding‐based retrieval. Intermediate to expert proficiency in Python (NumPy, Pandas, SpaCy, scikit‐learn, PyTorch/TF2, Hugging Face Transformers). Understanding of ML & Deep Learning models, including architectures for NLP (transformers), GNNs, and multimodal systems. Solid understanding of database ...

again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions ...

incubations or complex deep‐tech cross‐functional initiatives with measurable outcomes. Expertise in Python and deep experience with deep‐learning frameworks (e.g., Jax, TensorFlow, PyTorch) and state‐of‐the‐art ML techniques. Practical experience with modern AI paradigms such as world models, foundation models, multi‐modal language models, agent‐based ...

retrieval orchestration. Experience with evaluation datasets, benchmarking, annotation workflows, and advanced programming skills in Python. Familiarity with modern AI/ML frameworks and tooling (PyTorch, Hugging Face, LangChain, LangGraph, Haystack). Experience working with large‐scale datasets, distributed data/ML platforms, and production AI systems. Strong understanding of statistical ...

peers in ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps architecture. Willingness to learn new parts of the ML tech stack – Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and model serving frameworks. Fluency in life sciences or drug discovery is a plus. Working ...

Computer Science (or equivalent proven track record). 4 + years working on large‐scale ML codebases. Hands‐on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline chops. ...

technical leadership Deep expertise in a relevant technical domain such as ML systems, data pipelines, backend engineering, or cloud infrastructure Hands‐on experience with PyTorch, TensorFlow, or similar ML frameworks Strong understanding of scalable APIs, cloud‐native systems, and modern engineering practices Experience creating Proof of Concepts and evaluating technical ...