1 to 25 of 38 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. PyTorch, TensorFlow). 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 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. PyTorch, TensorFlow). 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 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 ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s More ❯

NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow, JAX, or similar). Demonstrated ability to work independently on real-world projects. Strong communicator, with the ability to share ideas, take feedback, and collaborate effectively. A master’s 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 ❯

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 ❯

industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision tasks and concepts, with direct experience working with YOLO models being a major plus. More ❯

industry. Expert-level proficiency in Python and extensive experience with data science libraries such as Pandas, NumPy, and Scikit-learn. Deep hands-on experience with deep learning frameworks, particularly PyTorch . Proven experience with statistical analysis , hypothesis testing, and data visualization techniques. Familiarity with computer vision tasks and concepts, with direct experience working with YOLO models being a major plus. More ❯

generative AI. Able to contextualise these techniques in industry settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful … experience in machine learning and/or data science roles Solid understanding of MLOps and production deployment practices Experience with Python and core ML libraries (e.g., Scikit-learn, Pandas, PyTorch, TensorFlow) Familiarity with cloud platforms and data infrastructure (e.g., AWS/GCP/Azure, SQL, ELT tools) Understanding of ethical frameworks, explainability, and governance in AI Engaging & Adaptable Communication: Ability More ❯

reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯

reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯

GCP/AWS/Azure, MySQL, Firestore, Docker/Kubernetes, CI/CD, IaC • Champion security best practices in a regulated space • Explore AI & machine learning (LLMs, LangChain, TensorFlow, PyTorch) What you’ll bring: • Strong React & Python (FastAPI/Django/Flask) experience • Solid API design & database skills • Start-up or scale-up mindset, adaptable and hands-on • Passion for More ❯

GCP/AWS/Azure, MySQL, Firestore, Docker/Kubernetes, CI/CD, IaC • Champion security best practices in a regulated space • Explore AI & machine learning (LLMs, LangChain, TensorFlow, PyTorch) What you’ll bring: • Strong React & Python (FastAPI/Django/Flask) experience • Solid API design & database skills • Start-up or scale-up mindset, adaptable and hands-on • Passion for More ❯

Reliable LLM/RAG/Agentic systems Bonus Points: Experience with fine-tuning embedding models Published papers in NLP, representation learning, or related fields Familiarity with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with vector databases and similarity search systems What You’ll Work On: Design and implement advanced semantic caching systems Develop and optimize embedding-based retrieval mechanisms More ❯

Reliable LLM/RAG/Agentic systems Bonus Points: Experience with fine-tuning embedding models Published papers in NLP, representation learning, or related fields Familiarity with modern ML frameworks (PyTorch, TensorFlow, Hugging Face) Experience with vector databases and similarity search systems What You’ll Work On: Design and implement advanced semantic caching systems Develop and optimize embedding-based retrieval mechanisms More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

cross-functional teams to turn real-world problems into working software. 🛠️ What You Bring: Fluency in Python and strong grasp of ML/DL concepts. Experience with frameworks like PyTorch, TensorFlow, Scikit-learn, and HuggingFace Transformers. Comfort designing production-ready AI systems—optimising for speed, cost, and value. Passion for leveraging AI assistants and agentic tools to maximise impact. Bonus More ❯

state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX. Managing and processing large-scale datasets and implementing advanced data augmentation strategies. More ❯

state-of-the-art models for a variety of computer vision tasks, including detection, segmentation, and classification. Writing highly efficient, scalable, and production-ready code in Python using the PyTorch framework. Optimizing models for high-performance inference on diverse hardware using tools like NVIDIA TensorRT, OpenVINO, and ONNX. Managing and processing large-scale datasets and implementing advanced data augmentation strategies. More ❯

For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI-driven industries such as AI drug discovery, AdTech, ML health-tech, research labs More ❯

For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI-driven industries such as AI drug discovery, AdTech, ML health-tech, research labs More ❯