25 of 25 PyTorch Jobs in Central 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 ❯

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 ❯

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 ❯

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 ❯

Science, Computer Science, Biostatistics, or related field ✔️ 7–10 years’ experience, with 3+ years applying AI/ML to healthcare or clinical research data ✔️ Expertise in Python, R, TensorFlow, PyTorch, and modern ML frameworks ✔️ Hands-on experience with LLMs, generative AI, and natural language processing for medical text ✔️ Familiarity with AWS, MLOps, and cloud-based platforms ✔️ Proven ability to partner More ❯

Science, Computer Science, Biostatistics, or related field ✔️ 7–10 years’ experience, with 3+ years applying AI/ML to healthcare or clinical research data ✔️ Expertise in Python, R, TensorFlow, PyTorch, and modern ML frameworks ✔️ Hands-on experience with LLMs, generative AI, and natural language processing for medical text ✔️ Familiarity with AWS, MLOps, and cloud-based platforms ✔️ Proven ability to partner More ❯

Science, Computer Science, Biostatistics, or related field ✔️ 7–10 years’ experience, with 3+ years applying AI/ML to healthcare or clinical research data ✔️ Expertise in Python, R, TensorFlow, PyTorch, and modern ML frameworks ✔️ Hands-on experience with LLMs, generative AI, and natural language processing for medical text ✔️ Familiarity with AWS, MLOps, and cloud-based platforms ✔️ Proven ability to partner More ❯

to AI/ML and serverless computing. Proficiency in JavaScript, TypeScript, Node.js, React.js, and Express.js for building full-stack applications. Experience with AI/ML frameworks such as TensorFlow, PyTorch, OpenAI API, or LangChain. Knowledge of microservices architecture, containerization (Docker, Kubernetes), and event-driven patterns. Strong understanding of API design, including REST, GraphQL, and WebSockets. Familiarity with DevOps practices, CI 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 ❯

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 ❯

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 ❯

statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability to create More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps 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 ❯

inference endpoints. Support pre-sales efforts, workshops, and proof-of-concepts alongside go-to-market teams. AI & ML Engineering Implement and optimise AI/ML models using frameworks like PyTorch, HuggingFace, LangChain, and NVIDIA Triton. Fine-tune foundation models for domain-specific use cases. Deploy and maintain inference services using REST/gRPC APIs, containerised and distributed systems. Data & Knowledge More ❯

deliver transformative, compliant, and ethical AI solutions. Requirements: Proven experience leading AI initiatives in banking, capital markets, or insurance. Deep technical expertise in generative AI technologies and frameworks (e.g., PyTorch, TensorFlow, Hugging Face). Strong business acumen and ability to align AI with client goals. Excellent leadership, communication, and stakeholder management skills. Passion for innovation and staying ahead of AI More ❯

a fund within financial services with a strong background in machine learning or a related field. Proficiency in Python/R and experience with deep learning frameworks such as PyTorch or TensorFlow will also be required. Want to join? Get in touch. Salary and total compensation is purely based on performance of your models and the overall business – we can More ❯

in perception for robotics or autonomous systems. Strong experience in computer vision, human pose estimation, and intent prediction. Knowledge of safety-related perception standards. Proficiency with machine learning frameworks (PyTorch/TensorFlow). Experience integrating perception into real-time safety systems. What We Offer: Competitive salary plus participation in our Stock Option Plan Paid vacation with adjustments based on your More ❯

Ready to take your ML skills from experiment to impact? Are you a Machine Learning Engineer who’s passionate about building real-world solutions that make a difference, not just proof-of-concept models gathering dust? You’ll be at More ❯

This isnt your average ML infrastructure role - it sits right at the intersection of cloud engineering and machine learning. Youll be building out ML nodes, optimising training workloads in PyTorch, and deploying them across containerised environments with Kubernetes and Docker. As the go-to person for ML and cloud, youll design and manage scalable, GCP environments, and set up the … week in London for the first few months. What theyre looking for Strong experience in cloud infrastructure engineering (GCP, AWS, or Azure is fine) Deep hands-on experience with PyTorch and other ML frameworks. Kubernetes and Docker expertise at scale. Experience with training models. Experience setting up CI/CD pipelines for ML or data-heavy workloads. Someone who has More ❯

This isnt your average ML infrastructure role - it sits right at the intersection of cloud engineering and machine learning. Youll be building out ML nodes, optimising training workloads in PyTorch, and deploying them across containerised environments with Kubernetes and Docker. As the go-to person for ML and cloud, youll design and manage scalable, GCP environments, and set up the … week in London for the first few months. What theyre looking for Strong experience in cloud infrastructure engineering (GCP, AWS, or Azure is fine) Deep hands-on experience with PyTorch and other ML frameworks. Kubernetes and Docker expertise at scale. Experience with training models. Experience setting up CI/CD pipelines for ML or data-heavy workloads. Someone who has More ❯

role This isnt your average infrastructure role - it sits right at the intersection of cloud engineering and machine learning. Youll be building out ML nodes, optimising training workloads in PyTorch, and deploying them across containerised environments with Kubernetes and Docker. As the go-to person for cloud, youll design and manage scalable, multi-cloud environments (AWS, GCP, Azure) and set … time, 5 days a week in their London office. What theyre looking for Strong experience in cloud infrastructure engineering (multi-cloud is ideal). Deep hands-on experience with PyTorch and other ML frameworks. Kubernetes and Docker expertise at scale. Experience setting up CI/CD pipelines for ML or data-heavy workloads. Someone who has worked with ML workloads More ❯

role This isnt your average infrastructure role - it sits right at the intersection of cloud engineering and machine learning. Youll be building out ML nodes, optimising training workloads in PyTorch, and deploying them across containerised environments with Kubernetes and Docker. As the go-to person for cloud, youll design and manage scalable, multi-cloud environments (AWS, GCP, Azure) and set … time, 5 days a week in their London office. What theyre looking for Strong experience in cloud infrastructure engineering (multi-cloud is ideal). Deep hands-on experience with PyTorch and other ML frameworks. Kubernetes and Docker expertise at scale. Experience setting up CI/CD pipelines for ML or data-heavy workloads. Someone who has worked with ML workloads More ❯

your average ML infrastructure role - it sits right at the intersection of cloud engineering and machine learning. Youll be building out ML nodes, training models, optimising training workloads in PyTorch, and deploying them across containerised environments with Kubernetes and Docker. As the go-to person for ML and cloud, youll design and manage scalable, GCP environments, and set up the … week in London for the first few months. What theyre looking for Strong experience in cloud infrastructure engineering (GCP, AWS, or Azure is fine) Deep hands-on experience with PyTorch and other ML frameworks. Kubernetes and Docker expertise at scale. Experience with training models (ideally image or video models). Experience in training models is a must! If you have More ❯