1 to 25 of 75 Permanent PyTorch Jobs in the City of London

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering More ❯

natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering More ❯

presentations to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

presentations to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms More ❯

automation tools. REQUIREMENTS: 4+ years of experience in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows More ❯

production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms More ❯

managing ML in production. What we’re looking for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers More ❯

managing ML in production. What we’re looking for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers More ❯

operations (ideally, experience governing AI models in production environments) Expertise across cloud platforms (AWS, Azure, GCP), Kubernetes, and containerised systems. Strong technical skills in Python, Java/Go, TensorFlow, PyTorch, and data engineering. Proven ability to engage directly with CxO-level stakeholders. Experience in MLOps, AI governance, and large-scale deployment. Recognised professional certifications in AI or cloud technologies. If More ❯

Kubernetes, MLflow, Weights & Biases]. Solid understanding of vector databases and their application in RAG systems. Strong communication and collaboration skills. Preferred Qualifications Experience with low-level ML frameworks [PyTorch, TensorFlow] for fine-tuning LLMs. Experience with speech recognition systems [e.g., Whisper] or computer vision models. Contributions to open-source AI projects. Experience with cloud platforms [AWS, GCP, Azure]. More ❯

Kubernetes, MLflow, Weights & Biases]. Solid understanding of vector databases and their application in RAG systems. Strong communication and collaboration skills. Preferred Qualifications Experience with low-level ML frameworks [PyTorch, TensorFlow] for fine-tuning LLMs. Experience with speech recognition systems [e.g., Whisper] or computer vision models. Contributions to open-source AI projects. Experience with cloud platforms [AWS, GCP, Azure]. More ❯

and Jupyter Notebooks Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights for coaches More ❯

skills, with the ability to present complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and a strong commitment to More ❯

solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯

skills, with the ability to present complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and a strong commitment to More ❯

position sits between the engineering and the investment team. You will wear multiple hats and leverage new AI and ML technologies. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools (Tableau or similar More ❯

position sits between the engineering and the investment team. You will wear multiple hats and leverage new AI and ML technologies. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools (Tableau or similar More ❯

in Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this More ❯

in Reinforcement Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this More ❯

deployment needs Implement and optimise ML solutions using Python, open-source tools & infrastructure Collaborate with cross-functional teams to enhance product features, based on client feedback Work with Python, PyTorch, Tensorflow, Kubernetes, Docker & cloud platforms Ideal Candidates have 5+ years of Backend (Python) Software Engineering experience in a fast-paced, high-growth, product environment, ideally as a Co-Founder or More ❯

building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and awareness of emerging More ❯

building interactive dashboards and reporting tools. • Familiarity with data engineering, ETL processes, and data pipelines. • Experience with statistical modelling and machine learning techniques, and libraries such as scikit-learn, PyTorch, or TensorFlow. • Excellent communication skills—able to explain complex analysis to non-technical stakeholders. • Proactive, inquisitive mindset with strong problem-solving skills. • Interest in cyber risk and awareness of emerging More ❯