351 to 375 of 955 TensorFlow Jobs in England

Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to … Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot More ❯

Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc You'll be skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to … Azure ML, Azure Stream Analytics, Cognitive services, Event Hubs, Synapse, and Data Factory) Fluency in common data science coding capabilities such as Python and modelling frameworks such as Pytorch, Tensorflow etc. Skilled in application of MLOps frameworks within a production environment Excellent communication skills, both verbal and written Strong time management and organisation skills Ability to diagnose and troubleshoot More ❯

as well as a strong background in AI research and applied machine learning. Expertise in key data science technologies and techniques, such as Python, Git, AWS, AWS Sagemaker, PyTorch, TensorFlow, Jax, Numpy, Scikit-learn, Time-series forecasting, Classification, Regression, Large-language models, and Experiment Design. Strong stakeholder management skills and the ability to communicate complex ideas to a diverse More ❯

advances in temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models More ❯

and 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 More ❯

internal teams. Technical Skills: Proficiency with open-source tools and technologies. Languages & Libraries: Python, R, Pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels. NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (as applicable). Visualization tools: Plotly, Seaborn, Matplotlib, Dash, Streamlit. Preferred Qualifications: Fluency in French or German is a strong advantage for future client engagements. Additional Information More ❯

and surprise us again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong More ❯

and 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 More ❯

insights. Machine Learning Engineer Key Skills Required: Comprehensive understanding of the full machine learning lifecycle, from development to production. Experience deploying machine learning models using frameworks like Scikit-learn, TensorFlow, or PyTorch. Proficiency in Python and adherence to software engineering best practices. Strong technical expertise in cloud architecture, security, and deployment, with experience in Azure. Hands-on experience with More ❯

Responsibilities: Develop and manage automated machine learning pipelines, CI/CD workflows, and orchestration frameworks for production-ready systems. Design and implement robust model deployment using platforms like TorchServe, TensorFlow Serving, or Triton for reliable inference delivery. Create low-latency, high-throughput inference systems with a focus on performance and scalability. Implement seamless deployment processes with A/B More ❯

machine learning, deep learning, and AI, especially in LLM and RAG technologies, with knowledge of LLM Agents, explainable AI, and graph ML as a plus. Proficiency in Python, PyTorch, TensorFlow, and data science libraries, along with development skills in Docker, Linux, GitHub/Gitlab, GPUs, and cloud services. Knowledge of knowledge graphs and graph databases like Neo4j is highly More ❯

years of experience in data science or machine learning roles. Strong knowledge of behaviour biometrics or sensor-based or time series data. Solid Python skills (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch). Experience with time-series data or sensor-based or behavioural biometric data, and sequential modelling (e.g., LSTMs, Transformers). Comfortable working with SQL and data visualisation More ❯

Deep understanding of computer vision techniques for detection and localisation. Strong experience working with embedded or constrained compute platforms. Proficiency in Python and major machine learning frameworks (e.g., PyTorch, TensorFlow). Experience with version control (Git), containerisation (Docker), and cloud technologies (e.g., AWS). Experience with building and maintaining end-to-end ML pipelines. Degree (BSc, MSc, or PhD More ❯

Looking For 5+ years of experience in data science, machine learning, or a related field. Strong proficiency in Python (or R) and experience with ML frameworks like scikit-learn, TensorFlow, or PyTorch. Deep experience in building and deploying models at scale. Solid understanding of statistics, experimentation, and data storytelling. Experience working with cloud environments (AWS, GCP, or Azure). More ❯

Excellent coding skills in languages such as Python, R. Significant industrial experience in data science with a focus on graph machine learning and experience with ML frameworks like PyTorch, TensorFlow, or DGL. Hands-on industrial experience with extracting insight from graph databases such as Neo4j Enterprise. Significant hands-on industrial experience with applied machine learning domains such as deep More ❯

including handling of large data sets, modelling and evaluation Good understanding of software engineering concepts, particularly with machine learning development Experience with machine learning Python frameworks such as PyTorch, Tensorflow and Scikit-Learn For more senior candidates: Understanding of, including published work within, related academic fields such as NLP, Computer Vision or Deep Learning Relevant industry experience with demonstrable More ❯

an R&D context. Plusses: Experience working with foundation models or self-supervised learning techniques applied to biological or image data. Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with cell-level microscopy (e.g., Cell Painting, HCS) and downstream biological interpretation. Understanding of model feedback loops — such as collaborating with ML teams to refine models based More ❯

an R&D context. Plusses: Experience working with foundation models or self-supervised learning techniques applied to biological or image data. Familiarity with deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with cell-level microscopy (e.g., Cell Painting, HCS) and downstream biological interpretation. Understanding of model feedback loops — such as collaborating with ML teams to refine models based More ❯

AI, particularly in LLM and RAG technologies, with knowledge of LLM Agents, explainable AI and/or graph ML as a plus. Proficiency in Python, PyTorch and/or Tensorflow, and popular data science libraries, as well as development skills with Docker, Linux, GitHub/Gitlab, GPUs, and cloud services. Exposure to knowledge graphs and graph databases such as More ❯

you if you: ✅ Are a strong software engineer with deep knowledge of data structures, system design, OOP ✅ Have hands-on experience with LLMs , ML/DL frameworks like PyTorch, TensorFlow, LangChain ✅ Know how to deploy, monitor & optimise ML models in real-world systems ✅ Are comfortable with MLOps tooling (CI/CD, Docker, Kubernetes) & cloud platforms (GCP/AWS/ More ❯

you if you: ✅ Are a strong software engineer with deep knowledge of data structures, system design, OOP ✅ Have hands-on experience with LLMs , ML/DL frameworks like PyTorch, TensorFlow, LangChain ✅ Know how to deploy, monitor & optimise ML models in real-world systems ✅ Are comfortable with MLOps tooling (CI/CD, Docker, Kubernetes) & cloud platforms (GCP/AWS/ More ❯

very positively. Technical Requirements: Required: Strong foundation in machine learning algorithms, statistics, and data structures within relevant technical projects. Proficiency in programming languages, frameworks, and tools, such as Python, TensorFlow, PyTorch. Experience with data preprocessing, feature engineering, and model evaluation techniques. Highly Desirable: Experience working on aerospace-related projects Experience deploying MLOps solutions and working within CI/CD More ❯

Experience working with real-world data sets and building scalable models from big data Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow Experience with large scale distributed systems Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation More ❯

AI, particularly in LLM and RAG technologies, with knowledge of LLM Agents, explainable AI and/or graph ML as a plus. Proficiency in Python, PyTorch and/or TensorFlow, and popular data science libraries, as well as development skills with Docker, Linux, GitHub/Gitlab, GPUs, and cloud services. Exposure to knowledge graphs and graph databases such as More ❯

or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional More ❯