1 to 25 of 50 TensorFlow Jobs in Central London

standards. Required Skills & Qualifications Education: Bachelor’s or Master’s in Computer Science, Data Science, Mathematics, or related field. Programming: Strong proficiency in Python (TensorFlow, PyTorch, Scikit-learn), and experience with SQL. ML Expertise: Solid understanding of supervised/unsupervised learning, deep learning, and model evaluation techniques. Cloud & MLOps ...

scenario modeling, optimization, and evaluation metrics for performance and fairness. Proficiency in Python (pandas, NumPy, scikit-learn) and deep learning libraries (PyTorch or TensorFlow). Hands-on experience with LLMs, prompt engineering, fine-tuning, and retrieval-augmented generation (RAG) pipelines. Experience integrating ML models via APIs and embedding ...

science roles, with proven success in delivering end-to-end projects. Strong proficiency in Python , R , and data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Expertise in multi-cloud environments (AWS, Azure, GCP) including services like S3, BigQuery, Azure ML, etc. Solid understanding of data engineering principles ...

grasp of supervised/unsupervised methods, evaluation metrics, feature engineering, and model tuning. Proficiency in Python (pandas, NumPy, Scikit-learn); experience with PyTorch or TensorFlow for deep learning. Experience with API development and connecting AI systems to external platforms. Working knowledge in deep learning techniques, including CNNs, RNNs ...

/ML solutions, with a strong focus on Microsoft Azure. • Proficiency in Python and experience with relevant AI/ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Keras). • Demonstrated experience with Azure Machine Learning, including MLOps concepts, model registration, deployment (AKS, ACI), and monitoring. • Hands-on experience with Azure ...

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 ...

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 ...

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 ...

Data Science/AI roles. Hands‐on experience with advanced AI and end‐to‐end solutions. Strong Python/Java skills and familiarity with TensorFlow/PyTorch. Proficient in ML/DL models, databases, ETL, and data pipelines. Experience with cloud (AWS/Azure/GCP) and MLOps. Expertise ...

with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing ...

Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation, A/B testing ...

Experience: Proven track record of delivering solutions in a client-facing consulting environment. MLOps Expertise: Hands-on experience with tools such as MLflow, Kubeflow, TensorFlow Serving, or similar. Cloud Platforms: Proficiency in multi-cloud environments (AWS, Azure, GCP). DevOps & Automation: Strong knowledge of CI/CD pipelines, containerization ...

5+ years hands-on AI/ML experience across industries, including some time in a client-facing role Core tech stack: Python/Java, TensorFlow/PyTorch/scikit-learn, cloud AI services (AWS/GCP/Azure), ETL tools, and data visualization. Agentic AI edge – ideally familiar with ...

years' experience in ML/AI engineering or data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning ...

experience Experience with large-scale ML systems (model training, serving, platforms) Experience supporting or working inside ML research teams Familiarity with ML frameworks (PyTorch, TensorFlow etc) Experience building pipelines for scientific or healthcare data Knowledge of cluster compute, distributed training and GPUs Understanding of healthcare data or regulated environments ...

model design to validation, deployment, and monitoring. Technical Proficiency: Fluency in Python, SQL, or similar languages, and experience with deep learning frameworks such as TensorFlow, Keras, PyTorch, or MXNet. Agile & DevSecOps: Familiarity with Agile methodologies and DevSecOps practices, including Git for version control. Cloud Platforms: Exposure to Azure ...

production optimisation for RAG systems, including latency, token cost control, context window constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field ...

production optimisation for RAG systems, including latency, token cost control, context window constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field ...

language processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ● Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ● Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ● Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. ...

analytics roles. • Recognised as a technical expert by colleagues, partners and customers. • Strong hands-on knowledge of AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn. • Experience working with cloud AI platforms (AWS, Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based ...

analytics roles. • Recognised as a technical expert by colleagues, partners and customers. • Strong hands-on knowledge of AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn. • Experience working with cloud AI platforms (AWS, Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based ...

Proficiency with TypeScript, Node.js, and modern JavaScript frameworks for UI development. Strong hands-on experience with Python, SQL, and AI/ML frameworks (e.g., TensorFlow, PyTorch), particularly within financial workflows. To apply for this role please submit your CV or contact Dillon Blackburn on (phone number removed ...

Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...

Docker, Kubernetes, Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/ ...