1 to 25 of 61 Permanent PyTorch Jobs in London

organisation. Required Experience & Skills AI/Technical Strong experience building and deploying machine learning and AI solutions in production. Hands‐on experience with: Python (PyTorch, TensorFlow, scikit‐learn) Data engineering tools (SQL, Spark, Airflow or similar) LLMs, NLP, and document intelligence (e.g. RAG, embeddings) Experience with cloud platforms (AWS, Azure ...

GenAI Ecosystem Lead the design and deployment of scalable AI solutions across Python, .NET, and cloud-native platforms Drive adoption of advanced frameworks (PyTorch, TensorFlow, Hugging Face, LangChain) Oversee integration of LLMs (OpenAI, Anthropic, Gemini, Mistral) via enterprise platforms (Azure OpenAI, Vertex AI) Implement RAG architectures and manage vector databases ...

deploying AI applications in large scale production environments. Experience managing data science teams and couching team members Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). Hands-on experience with agentic frameworks (LangChain, CrewAI, AutoGen, LangGraph, ADK). Experience with generative models (transformers, GANs/VAEs; diffusion models ...

data workflows for maximum scalability and cost-efficiency. Insurance Domain experience is added advantage. Your Technical Toolkit AI/ML: Expert proficiency in Python, PyTorch/TensorFlow, and GenAI frameworks like LangChain, LlamaIndex, or CrewAI. Data Architecture: Hands-on experience with Vector Databases (e.g., Pinecone, Milvus, Weaviate) and SQL/ ...

BI. Published work, patents or conference presentations related to AI or data science in finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, Jupyter notebooks and version control (Git). Machine Learning: regression, classification, clustering, tree‐based models, neural networks, MLOps practices and model deployment. Data ...

with emerging machine learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

. Published research, patents, or conference presentations in AI or data science related to finance. Technical Skills Programming: Python (pandas, scikit‐learn, TensorFlow/PyTorch), R, SQL, notebooks, Git. Machine Learning: regression, classification, clustering, tree‐based models, neural networks; MLOps, model deployment, automated testing. Data Platforms: relational databases, NoSQL, time ...

learning solutions for personalizing recommendations. Hands-on experience building training frameworks and/or serving large-scale models using tools such as Tensorflow or PyTorch is a plus. You stay up-to-date with the state-of-the-art open source infrastructure solutions applicable to designing and improving large scale ...

building, deploying, and maintaining ML systems in production, beyond research prototypes. Strong Python skills and hands-on experience with modern ML frameworks such as PyTorch or TensorFlow and MLOps frameworks such as ClearML, Flyte, and MLFlow. Demonstrated experience across the full ML lifecycle: data preparation, training, evaluation, deployment, monitoring ...

data scientist (or similar role). Expert proficiency of Python and experience using SQL, alongside using common ML/AI packages (TensorFlow, PyTorch, XGBoost, etc.). Familiarity with statistical (e.g. GLM, GAMs) and deep learning techniques (e.g. neural networks, transformers, diffusion models, etc.). Comfortable designing and creating neural network ...

deliver features Skills & Experience: Strong Python and SQL skills Familiarity with Azure or AWS Some exposure to ML frameworks (e.g. scikit-learn, TensorFlow, or PyTorch) Background in data engineering, analytics engineering, or similar Desirables: ETL/ELT pipeline experience Microsoft Fabric/Data Lake knowledge BI tools (e.g. Power ...

Hands-on with; LLMs (OpenAI, Llama, Claude, Mistral), Vector DBs (Pinecone, Weaviate, FAISS), Frameworks (LangChain, LlamaIndex, AutoGen, CrewAI, LangGraph) Strong Python + ML frameworks (PyTorch/TensorFlow) Experience deploying on AWS, Azure, or GCP Experience leading or influencing technical teams Nice to have: Experience in consulting/client-facing roles ...

reviews, and testing strategies. Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build ...

Backend: Node.js, Python, REST & GraphQL APIs Cloud & Infra: AWS (ECS, S3, Lambda), Docker, Cloudformation, Pulumi, CI/CD with GitHub Actions ML/AI: PyTorch, TensorFlow, scikit‐learn, MLflow for experiment tracking, Zenml for ML pipelines Data: PostgreSQL, DynamoDB, data pipelines with Zenml (We’re open to evolving the stack ...

control tools, preferably Git. Proficiency in Docker and container orchestration. Advanced proficiency in Python and familiarity with AI and machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of algorithms, data structures, and software engineering principles. Experience in deploying AI models in a production environment. Proven ability ...

tooling stack What They’re Looking For 4+ years experience in machine learning, data science, or AI engineering Strong Python skills (NumPy, Pandas, PyTorch/TensorFlow) Experience working with biological or biomedical data (industry or academia) Solid understanding of ML fundamentals (supervised/unsupervised learning, model evaluation, etc.) Familiarity with ...

quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian inference, APIs, SQL) Experience leading ...

Data Scientist with production ML exposure Strong understanding of ML algorithms, model development, and deployment Experience with Python and ML frameworks (e.g. TensorFlow, PyTorch, scikit-learn) Familiarity with data pipelines and cloud or on-prem environments Understanding of MLOps principles Ability to work in secure or regulated environments Eligibility Must ...

ICLR. Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets. Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.). Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain. Why Apply Compensation and total rewards ...

understanding of system design: orchestration, memory, deployment, monitoring – Exposure to tools such as LangGraph, ReAct, CoT — or building similar systems from scratch – Familiar with PyTorch/TensorFlow, RAG architectures, vector databases, modern cloud infra – Experience in startup or consulting environments is a plus – Comfortable working autonomously in fast-moving, sometimes ...

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 ...

/or distributed compute environments Experience with GPU scheduling/orchestration (e.g., Kubernetes schedulers - Volcano, Ray, etc.) Experience supporting ML workloads or training pipelines (PyTorch, TensorFlow, etc.) Experience with multi-cloud or hybrid cloud environments Background in performance optimization for training workloads Experience in robotics, simulation, or embodied AI systems ...

distributed systems, networking, and system reliability Demonstrated ability to lead large technical initiatives and influence system design Experience supporting ML workloads or training pipelines (PyTorch, TensorFlow, etc.) Nice to have: Experience with multi-cloud or hybrid cloud environments Background in performance optimization for large-scale training workloads Experience in robotics ...

Communication: Ability to collaborate across disciplines and present technical findings clearly. Bonus Points: A PhD in Chemistry or Computer Science , experience with RDKit/PyTorch , or a track record of open-source contributions. Why Join? Equity: A competitive option plan aligned with the early stage of the company. Modern Benefits ...

experience in process digitization using AI technologies.- Strong background in AI software development and deployment.- Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).- Excellent problem-solving and analytical skills.Skills:- Artificial Intelligence- Machine Learning- Python- AI Application Development- Workflow Automation- Process Digitization- Software Development- Deep LearningPandoLogic. ...