1 to 25 of 77 Remote TensorFlow Jobs in London

of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL, and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Experience More ❯

applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data Engineering Skills: Proficiency in developing and maintaining real-time data pipelines for processing large-scale data. Experience with ETL More ❯

and multi-agent systems (MAS). Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or More ❯

computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms - demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯

business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We More ❯

related field (or equivalent experience). Preferred Qualifications: Advanced degree (Master's or Ph.D.) in a relevant field. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of data visualization tools (e.g., Tableau, Power BI). Familiarity with version control systems (e.g., Git). More ❯

related field (or equivalent experience). Preferred Qualifications: Advanced degree (Master's or Ph.D.) in a relevant field. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of data visualization tools (e.g., Tableau, Power BI). Familiarity with version control systems (e.g., Git). More ❯

ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment More ❯

ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment More ❯

or a related field. Proficiency in programming languages like Python, R, or SQL for data manipulation. Experience building machine learning models using libraries like TensorFlow, PyTorch, or scikit-learn. Familiarity with cloud platforms like AWS, GCP, or Azure. Strong written and spoken English skills. Bonus Experience: Experience with big More ❯

in Bayesian inference and probabilistic modeling : PGMs, HMMs, GPs, MCMC, variational methods, EM algorithms, etc. Proficiency in Python (must) and familiarity with PyMC, NumPyro, TensorFlow Probability , or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods More ❯

timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques More ❯

in top-tier conferences (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL, ICLR). Familiarity with one or more deep learning frameworks (e.g. pytorch, jax, tensorflow, ) Experience in ML Research beyond completing a PhD (e.g. supervision, industry experience, leading academic initiatives, ). Excellent communication skills to report and present research More ❯

Experience working with ML models and their deployment. Familiarity with ML infrastructure, feature stores, and MLOps best practices. Exposure to deep learning frameworks (PyTorch, TensorFlow). Experience with building internal tools, dashboards, or lightweight front-end components (e.g., Streamlit, Dash, or BI tools like Looker, Tableau) or JavaScript frameworks More ❯

understanding of industry trends, concepts, opportunities, threats & constraints. Experience & knowledge of GenAI, predictive analytics, or automation workflows in enterprise environments. Familiarity with NLP frameworks (TensorFlow, PyTorch) and LLM fine-tuning techniques. ITIL certification and/or AI/ML certifications (AWS, Google Cloud). Experience with implementing scripted web More ❯

understanding of industry trends, concepts, opportunities, threats & constraints. Experience & knowledge of GenAI, predictive analytics, or automation workflows in enterprise environments. Familiarity with NLP frameworks (TensorFlow, PyTorch) and LLM fine-tuning techniques. ITIL certification and/or AI/ML certifications (AWS, Google Cloud). Experience with implementing scripted web More ❯

Implementing MLOps best practices for seamless model deployment, monitoring, and iteration. What We’re Looking For: 🔹 Strong Python skills – You know your way around TensorFlow, PyTorch, or Hugging Face. 🔹 Experience with LLMs, NLP, or recommendation algorithms . 🔹 Familiarity with MLOps, APIs, and scalable cloud solutions . 🔹 Passion for AI More ❯

Implementing MLOps best practices for seamless model deployment, monitoring, and iteration. What We’re Looking For: 🔹 Strong Python skills – You know your way around TensorFlow, PyTorch, or Hugging Face. 🔹 Experience with LLMs, NLP, or recommendation algorithms . 🔹 Familiarity with MLOps, APIs, and scalable cloud solutions . 🔹 Passion for AI More ❯

production environment. Practical experience in implementing ML systems using languages like Python or Scala and are familiar with relevant ML libraries and frameworks (e.g., TensorFlow or PyTorch). Solid understanding of various machine learning algorithms (e.g., classification, regression, clustering) and their practical applications. Proficient in data manipulation and analysis More ❯

production environment. Practical experience in implementing ML systems using languages like Python or Scala and are familiar with relevant ML libraries and frameworks (e.g., TensorFlow or PyTorch). Solid understanding of various machine learning algorithms (e.g., classification, regression, clustering) and their practical applications. Proficient in data manipulation and analysis More ❯

skills and attention to detail Strong communication skills and ability to work in a collaborative environment Bonus Skills: Experience with AI/ML libraries (TensorFlow, PyTorch, scikit-learn) Knowledge of cloud platforms (AWS, GCP, Azure) Familiarity with containerisation (Docker) Experience with CI/CD pipelines Understanding of the built More ❯

skills and attention to detail Strong communication skills and ability to work in a collaborative environment Bonus Skills: Experience with AI/ML libraries (TensorFlow, PyTorch, scikit-learn) Knowledge of cloud platforms (AWS, GCP, Azure) Familiarity with containerisation (Docker) Experience with CI/CD pipelines Understanding of the built More ❯

financial analysis, modelling, and statistics, with experience extracting insights from heterogeneous multi-dimensional datasets. Ability to apply machine learning techniques (e.g., scikit-learn, PyTorch, TensorFlow) and present complex data visually using Matplotlib, seaborn, or Streamlit. Fluent in Python, with experience working with data processing libraries such as Pandas. Strong More ❯

related field 5+ years of experience in AI development Strong understanding of AI principles, machine learning algorithms, and natural language processing Experience with Python, TensorFlow, and PyTorch Excellent communication and teamwork skills Fluent in English More ❯