23 of 23 TensorFlow Jobs in Central London

building robust automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model ...

identify and validate use cases. Essential Skills At least 6-10 years of hands-on development and architectural experience. Proficiency in Python, PyTorch, TensorFlow, or similar frameworks. experience with supervised, unsupervised, and reinforcement learning. Solid grounding in Natural Language Processing (NLP) concepts such as tokenisation, embeddings, semantic search, text ...

commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed‐integer, reinforcement learning desirable). Strong ...

ethics and bias mitigation, with experience in implementing strategies to ensure air and unbiased AI solutions. • Serverless Computing and Distributed Systems • Deep Learning Frameworks (TensorFlow, PyTorch) • Innovation and Emerging Technology Trends • Strategic AI Vision and Roadmapping • Enthusiastic about working in a fast-paced environment using the latest technologies ...

users) machine 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 ...

related field Strong software engineering skills: clean code, testing, debugging, version control, and system design Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow, or JAX) Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerisation (Docker, Kubernetes) Solid understanding of ML fundamentals (model training, evaluation ...

models together to achieve reliable results. True ML Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand ...

model serving, versioning, and lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Databricks Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services ...

experiment tracking and monitoring Collaborate with data scientists and engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools ...

machine learning, deep learning, and optimisation Hands-on experience training, evaluating, and deploying ML models in real-world systems Proficiency with PyTorch (preferred) or TensorFlow; familiarity with the Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines ...

like Time-Series Forecasting , Probabilistic Modelling , or Combinatorial Optimization . Technical Proficiency: Expert-level Python skills with deep experience in libraries such as PyTorch, TensorFlow, or Scikit-learn . Problem Solving: A track record of applying theoretical concepts to solve messy, real-world business problems. Communication: Ability to explain ...

technologies Required Skills & Experience MSc or PhD in Computer Science, Machine Learning, Mathematics, Statistics, or similar Strong Python programming skills Experience with PyTorch, TensorFlow, or optimisation libraries (e.g. Gurobi, OR-Tools) Strong technical communication and stakeholder engagement skills Ability to write clean, efficient, maintainable code Interest in explaining ...

libraries such as Neo4j, NetworkX, GraphX, or similar. Strong programming skills in Python & PySpark, with experience in relevant machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch). Expertise in graph algorithms including shortest path, centrality, community detection, and graph embeddings. Experience with big data technologies and cloud platforms ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands-on use of ML/DL frameworks (e.g., PyTorch , TensorFlow), including taking models from experimentation into production model serving. End-to-end MLOps experience, including CI/CD for ML, experiment tracking, model registries ...

ship impactful features quickly while ensuring safety and technical rigor. The ideal candidate: Strong background in Python and ML libraries like PyTorch or TensorFlow, with experience in supervised and reinforcement learning. Hands-on expertise in fine-tuning Large Language Models, prompt engineering, and deploying models within cloud environments like ...

Safety classifiers Behaviour-shaping or reward-modelling components. LLM and multimodal fine-tunes Adversarial robustness defences Use Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX, HuggingFace). Contribute to creation of synthetic datasets, adversarial evaluation corpora, and scenario-based test sets. Help transition research outputs into scalable controls … grasp of core Responsible AI concepts: Bias and fairness Explainability Privacy-preserving ML. Robustness and uncertainty Nice to have: Experience with ML frameworks: PyTorch, TensorFlow, Flax/JAX, HuggingFace. Exposure to multimodal models (CLIP, Whisper, LLaVA, video transformers). Familiarity with safety benchmarks, adversarial testing, red teaming, or uncertainty ...