1 to 25 of 93 TensorFlow Jobs in Central London

and 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 More ❯

in large language models (LLMs) and prompt engineering for business applications. Strong programming skills ( Python, R, Java ) for AI model development and deployment. Familiarity with AI libraries and frameworks (TensorFlow, PyTorch, Keras). Experience deploying AI models in cloud computing environments (AWS, Azure, Google Cloud). Deep understanding of enterprise AI architecture, data engineering, and model optimization . Strong More ❯

retraining mechanisms Conduct experiments using A/B testing and statistical analysis to validate approaches Document ML systems and provide support for ongoing performance tuning Use tools like Python, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, MLflow, Docker, SQL , and others Requirements Minimum Bachelors degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine … Learning Engineer or in a similar role (minimum 1 year ) Strong proficiency in Python and popular ML frameworks (e.g., TensorFlow, PyTorch) Experience deploying machine learning models into production environments Solid understanding of data structures , algorithms , and statistical learning Familiarity with cloud platforms (AWS, Azure, or GCP) and ML pipeline orchestration Bonus: Experience with deep learning , NLP , recommendation systems , or More ❯

/RFP process, as preferred 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. Terraform). Technology deployment– proven More ❯

managing technical or data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex More ❯

Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of More ❯

customers, and beyond. What will make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of A/B tests. • Familiarity More ❯

with data privacy regulations. Technical Skills required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such More ❯

engineering. ● Proven experience in working with financial data and developing AI/ML solutions for financial services applications. ● Expertise in Python and common machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). ● Strong understanding of data engineering principles and best practices. ● Excellent collaboration skills. ● Experience with cloud platforms such as AWS, Azure, or GCP. ● Experience with Agile development methodologies. More ❯

financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical More ❯

monitoring frameworks Participate in code reviews, design discussions, and performance tuning Requirements: 3+ years of experience in a Machine Learning Engineer or similar role Proficiency in Python , ML frameworks (TensorFlow, PyTorch), and deployment tools (Docker, MLflow, etc.) Experience building scalable ML pipelines in cloud environments (AWS, GCP or Azure) Familiarity with energy systems, smart metering, or IoT data is More ❯

programming languages such as Python. Experience with data visualization tools like Power BI. Familiarity with data manipulation libraries such as Pandas and NumPy. Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Excellent problem-solving skills and attention to detail. Ability to work effectively both independently and as part of a team. Strong communication skills, both written More ❯

not only technically strong, but solution-oriented, strategically minded, and able to communicate insights clearly to both technical and non-technical audiences. Requirements: Advance Python (Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch) & SQL skills. (Snowflake a plus) Experience with Data warehousing and database technologies Solid machine learning experience (modelling to deployment) Cloud exposure (GCP/AWS/Azure) Excellent More ❯

who is technically proficient, solution-oriented, strategically minded, and capable of communicating insights clearly to both technical and non-technical audiences. Requirements Advanced Python skills (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) & SQL (Snowflake a plus) Experience with Data warehousing and database technologies Solid experience in machine learning (modeling to deployment) Cloud exposure (GCP/AWS/Azure) Excellent communication More ❯

data mining; additional experience and knowledge of Big Data tools preferred. 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 visualisation and API libraries (matplotlib, plotly, streamlit, Flask, etc). Understanding of Gen AI models, Vector databases, Agents, and follow the market More ❯

/PhD in Computer Science, Data Science, Mathematics, or related field. 5+ years of experience in ML modeling, ranking, or recommendation systems . Proficiency in Python, SQL, Spark, PySpark, TensorFlow . Strong knowledge of LLM algorithms and training techniques . Experience deploying models in production environments. Nice to Have: Experience in GenAI/LLMs Familiarity with distributed computing tools More ❯

and data-driven features into production. Your Profile: Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong More ❯

tool technologies & technical architecture. Deep 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 services in ServiceNow, Java, and More ❯

a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and a desire to build systems More ❯

Domain experience in finance, insurance, or e-commerce is a plus but not required. - Experience deploying models in cloud environments. - Familiarity with machine learning frameworks and libraries such as TensorFlow, CatBoost, XGBoost, Scikit-learn, and Pandas. - Experience developing and integrating APIs. - Proficiency in SQL. - Background in software engineering and exposure to DevOps/MLOps practices. - Working knowledge of CI More ❯

lead end-to-end AI projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication skills and the More ❯

Create presentations and communicate complex findings to technical and non-technical stakeholders• Identify and explore new data sources and technologies to drive innovation Qualifications • Strong experience with Python, SQL, TensorFlow, PyTorch, GCP, Docker, and LLM technologies• Ability to solve complex, ambiguous problems with minimal guidance• Excellent communication skills for explaining technical concepts to non-technical audiences• Experience in team 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 ❯

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 ❯

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 ❯