1 to 25 of 226 PyTorch Jobs in London

field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with 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. 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. 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 ❯

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 ❯

lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment. Proficiency in programming languages, including Python. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc. Experience developing Python APIs using tools such as FastAPI. Knowledge of database technologies (SQL, MongoDB, Databricks) and data pipeline tools. Familiar with ML CI/CD pipelines More ❯

oriented programming and performance optimization Experience developing and deploying production machine learning applications on cloud platforms (GCP preferred, AWS and Azure acceptable) Familiarity with Python ML packages such as PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas Strong SQL skills for data preparation and feature engineering Knowledge of MLOps principles, including automated retraining, monitoring, and deployment strategies Basic understanding of More ❯

performance optimisation * Experience developing & deploying productionised Machine Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated More ❯

related quantitative field. - 4+ years of experience in developing and deploying machine learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both technical and non-technical 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 ❯

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 ❯

AI-assisted development tools such as Cursor, Claude Code, Codex, and GitHub Copilot for technical analysis, code generation and code review. Hands-on experience with AI/ML frameworks (PyTorch, TensorFlow, HuggingFace) and LLM orchestration tools (LangChain, LangGraph, or similar) Experience deploying ML models using containerised solutions (Docker, Kubernetes) and frameworks like BentoML or equivalent. Familiarity with vector databases and More ❯

Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in taking advanced statistical/ML solutions from prototype to production and delivering high-impact outcomes to complex business problems Proactive technical leader with a strong More ❯

in AI/ML, LLMs, and GenAI technologies. To Be Successful in The Role, You Will Have Required Skills: Proficiency in Python and machine learning framework s (e.g., TensorFlow, PyTorch, Scikit-Learn). Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation More ❯

of-the-art NLP and ML techniques Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch Extensive experience with Python and PyTorch Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency Experience with the full ML development More ❯

and non-technical audiences Ideally you have: • Experience as a Customer Engineer, Forward Deployed Engineer, Sales Engineer, Solutions Architect, or Technical Product Manager • Familiarity with AI frameworks such as PyTorch or TensorFlow • Contributions to open-source projects, particularly in the space of DevOps or AI Benefits We have local offices in Paris, London, Marseille and Singapore. France Competitive cash salary More ❯

years of experience in Software, Data, or ML engineering roles (preferred). You bring strong problem-solving skills, proficiency in Python, and familiarity with ML frameworks like TensorFlow or PyTorch . You have exposure to cloud platforms (e.g., AWS, GCP), containerization (Docker, Kubernetes), and scalable data systems (e.g., Spark, Kafka). You are experienced or interested in ML model serving More ❯

AI application is highly desirable Strong expertise in Generative AI, LLMs, or related NLP technologies Proficiency in Python and/or Scala; experience with ML libraries such as TensorFlow, PyTorch, HuggingFace, or scikit-learn Experience with Databricks, distributed data systems (e.g., Spark, Hadoop), and cloud platforms (AWS, GCP, or Azure) Ability to thrive in ambiguous environments, working closely with cross More ❯

their strategic value Qualifications Experience Extensive experience in data science, machine learning, or advanced analytics, ideally in a technical leadership role Proven expertise in Python and ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn) and experience across NLP, computer vision, and LLMs Strong statistical foundation, including A/B testing, causal inference, and experimental design Proficiency in SQL and working with More ❯

learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as they emerge. Experience of using Cloud technologies More ❯

and business analytics Hands-on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ Experience working with structured More ❯