14 of 14 TensorFlow Jobs in Central London

experience with various data science and machine learning libraries. Experience with libraries/frameworks like NumPy, Pandas, SciPy, Scikit‐learn, TensorFlow, PyTorch, Transformers, Langchain, Streamlit, or Gradio, among others. Experience with cloud‐based tools for production use (e.g., AWS SageMaker, AWS Bedrock, Vertex AI, Azure Machine Learning, Azure OpenAI ...

backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure Product-minded: you think ...

1+ year of commercial experience in machine learning or data science Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or XGBoost Exposure to AWS services (e.g. S3, Lambda, SageMaker) Understanding of core ML concepts: model evaluation, validation, and experimentation Familiarity with MLOps ...

healthcare). Track record of thought leadership (publications, patents, open source, or industry impact). Technical Excellence Expert Python and modern ML frameworks (PyTorch, TensorFlow). Strong experience with Generative AI tooling (e.g. LangChain, LangGraph or similar). Deep understanding of LLMs, prompt engineering, RAG, vector databases, evaluation ...

experience shipping AI or ML systems to a live production environment Solid Python across the core stack: Pandas, NumPy, Scikit-learn, and PyTorch or TensorFlow Real hands-on experience with LLMs — fine-tuning, prompt engineering, agentic orchestration A working understanding of MLOps: you don't just build models ...

Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g., MLflow, Weights & Biases, Data Version ...

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 ...

ICML, or ICLR. Hands-on experience applying deep learning models to complex, ideally temporal or financial, datasets. Expertise in Python and modern ML frameworks (TensorFlow, PyTorch, JAX, etc.). Prior experience in a commercial or industry setting post-PhD, ideally in a similarly data-driven domain. Why Apply Compensation ...

statistics, linear models & model evaluation techniques Experience with the Python data stack (NumPy, Pandas, etc.) and ML libraries Familiarity with tools such as PyTorch, TensorFlow, JAX, Plotly, Altair Experience working with large datasets and performance-sensitive systems Strong problem-solving ability with attention to detail Ability to communicate complex ...

strong background in machine learning or a related field. Proficiency in Python/R and experience with deep learning frameworks such as PyTorch or TensorFlow will also be required. Want to join? Get in touch. Salary and total compensation is purely based on performance of your models ...

following areas: Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost. Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe ...

you. What You’ll Do Own end-to-end ML model lifecycles from training to deployment to monitoring Productionise models built in PyTorch, TensorFlow, or Scikit‐learn Use MLflow for experiment tracking, model versioning, deployment, and release workflows Build scalable data & ML pipelines in Databricks (Delta, DLT, Jobs) Design … Work closely with engineering teams to deliver real-world ML systems across multiple sectors. Tech Stack You’ll Work With Python, SQL, PySpark PyTorch, TensorFlow, Scikit‐learn MLflow (core focus), Databricks, Azure IaC: Terraform, ARM, Ansible Git, Azure DevOps, Jenkins What We’re Looking For ✔️ 3+ years ...

frameworks and libraries. Collaborate closely with data scientists, engineers, and stakeholders to turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark … passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ML lifecycle tools (MLflow, Kubeflow, Azure ...

We are seeking a PhD Computer Vision Scientist with deep expertise in object detection, tracking, or related visual perception tasks. You’ll join our world-class research team to design, implement, and optimize algorithms that ...