1 to 25 of 140 TensorFlow Jobs in the UK excluding London

practices. Diagnose and resolve complex technical challenges in big data and ML systems. About You You're fluent in Python and experienced with leading ML/AI frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face). You have a solid background in MLOps: experiment tracking, CI/CD for ML, model versioning, deployment, and monitoring. You've built scalable backend More ❯

world use cases Contribute to code reviews, testing, and documentation Required Skills & Experience Strong proficiency in Python and its AI/ML ecosystem (e.g. NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with machine learning model development , training, and deployment Familiarity with LLMs , NLP , or computer vision techniques Solid understanding of software engineering principles and version control (Git) Experience working More ❯

the team. Skills and Experience: Degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and key libraries such as NumPy, Pandas, scikit-learn, TensorFlow or PyTorch. Basic understanding of machine learning algorithms and model evaluation techniques. Strong analytical and communication skills. Comfortable working in a collaborative environment and taking feedback. Desirable: MSc in More ❯

practices in machine learning. Optimization : Continuously improve machine learning infrastructure and production workflows. Strong technical foundation in machine learning and software engineering Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (AWS, GCP, Azure) Experience with CI/CD pipelines for machine learning (e.g., Vertex AI) Familiarity with data processing tools like Apache More ❯

core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed data More ❯

versioning Exposure to tools like KServe, Ray Serve, Triton, or vLLM is a big plus Bonus Points Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Qualifications Degree in Computer Science, Engineering, Data Science, or similar What We Offer A collaborative and innovative work More ❯

core software tooling: Git, Unix/Linux, Docker. Plus, a strong opinion on your IDE/editor of choice is welcome Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. Excellent communication skills; both in customer-facing and internal team communication. Knowledge of MLOps is not essential, but More ❯

platforms, and retrieval-augmented generation systems. Qualifications: 3+ years of experience delivering full-stack AI/ML applications in production. Proficiency in Python, especially with ML libraries such as TensorFlow, PyTorch, scikit-learn, and backend frameworks like FastAPI, Django, Flask. Experience with frontend frameworks: React, Vue, or Angular. Hands-on experience building and scaling ML models (LLMs, NLP, classification More ❯

meet deadlines, and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied mathematics and physics More ❯

Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

core software tooling: Git, Unix/Linux, Docker. Plus, a strong opinion on your IDE/editor of choice is welcome Familiarity with modern machine learning tools, for instance TensorFlow, Keras, PyTorch or SKLearn. Commercial experience with these is not essential. Excellent communication skills; both in customer-facing and internal team communication. Knowledge of MLOps is not essential, but More ❯

about building something new. You should have: 2+ years of experience in machine learning or data science roles Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms and statistical methods Experience working with cloud platforms (AWS, GCP, or Azure) Familiarity with MLOps tools and practices is a More ❯

learning engineers, AI researchers, and data scientists, driving end-to-end AI solution delivery. Designing and implementing AI architectures across cloud and on-prem environments, leveraging tools like PyTorch, TensorFlow, and Hugging Face. Spearheading the development of production ready AI models, from foundational LLMs to custom built cognitive agents, solving real world business challenges. Establishing scalable ML/AI More ❯

such as Python, R, C, C++, or Java, and their associated security considerations. * Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. * Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. * Strong More ❯

Python programmer in a short 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, for example, supervised/unsupervised More ❯

Python programmer in a short 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, for example, supervised/unsupervised More ❯

and big data engineering to productionizing classical ML and LLMs, you'll be at the core of AI infrastructure. Key Requirements: Expert in Python, ML/AI frameworks (PyTorch, TensorFlow, Hugging Face) Proven MLOps, big data, and backend/API development experience Deep understanding of NLP and LLMs Proficient with cloud platforms (AWS/GCP/Azure), Airflow, DBT More ❯

Computer Science, Engineering, or a related field with a strong ML focus. Solid understanding of deep learning architectures (CNNs, RNNs, Transformers). Proficiency in Python and ML libraries like TensorFlow, PyTorch, and scikit-learn. Strong experience with AWS services and cloud-native development. A proactive, collaborative mindset with a passion for learning and innovation. Bonus Points For Familiarity with More ❯

Experience with sports data is ideal but not essential. Familiarity with sports performance and biometric data analysis would be nice. Familiarity with machine learning frameworks and libraries, such as TensorFlow, PyTorch, or Scikit-learn. Any experience working with large, complex data sets and managing data pipelines, ensuring data quality and integrity. Some experience in data analysis, predictive modelling, or More ❯

applications. Required skills: Solid foundation in AI/ML principles (e.g. neural networks, NLP, transformers, speech processing). Hands-on experience with Python and popular ML frameworks (e.g. PyTorch, TensorFlow, Hugging Face). Familiarity with LLM APIs and open-source models (e.g. GPT, Claude, Mistral, Whisper). Familiarity with agentic AI frameworks (LangChain, AutoGen, CrewAI, OpenAI Functions). Interest More ❯

names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with data warehouse More ❯

names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with data warehouse More ❯

we need from you: Strong background in NLP and AI, particularly with LLMs and RAG-based solutions Proficiency in Python and modern AI/ML libraries (e.g. HuggingFace, LangChain, TensorFlow, PyTorch) Experience with data exchange and storage frameworks (e.g. APIs, SQL, NoSQL, Parquet) Track record of delivering technical solutions in Agile environments Excellent communication skills and a collaborative mindset More ❯

Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯