1 to 25 of 47 TensorFlow Jobs in Berkshire

organisation. Required Skills & Experience Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow More ❯

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 ❯

Engineering, Mathematics, or a related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion for building practical, scalable AI More ❯

on experience in data science and AI engineering. Proven track record of delivering AI software and deploying solutions in production. Strong proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Keras, Numpy, Pandas, Langchain, Pinecone, and more. Experience with cloud platforms and compute systems for model training and deployment. Excellent communication and strategic thinking skills. Preferred Experience More ❯

ML Skills: Proficiency in Python, 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 of developed AI components. Responsibilities More ❯

Proven experience designing and deploying MLOps pipelines (MLflow, Azure ML, Azure DevOps etc). Strong programming skills in Python and familiarity with common ML/AI libraries (scikit-learn, tensorflow, Keras etc.). Experience implementing machine learning and large language models (LLMs), encompassing deployment, monitoring, and retraining. Familiarity with software engineering guidelines: version control (e.g., Git), CI/CD More ❯

We’re Looking For: Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab More ❯

Cloud Platform (GCP) services, such as Vertex AI, BigQuery, Cloud Functions, and Cloud Storage. Strong programming skills in Python (preferred), Java, or similar languages, including experience with ML frameworks (TensorFlow, PyTorch, etc.). Familiarity with regulatory environments in banking/finance and understanding of regulatory change management processes. Knowledge of automation, workflow orchestration, and version control tools (e.g., Airflow More ❯

and training models in a distributed environment. LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker). Algorithms and data More ❯

models in a distributed environment. LLMs: Strong understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g. More ❯

models in a distributed environment. LLMs: Deep understanding of LLM architectures, pre and/or post-training, evaluations and inference. Programming languages: Excellent proficiency in Python using PyTorch/TensorFlow/JAX framework. Customer facing: Experience working directly with customers to solve applied problems, including product integration. Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g. More ❯

frameworks, and tooling, such as Python, R, Kubernetes, Kubeflow, JavaScript/JVM, Kafka Background in Application development, deployment, and monitoring on Kubernetes Proficient in PyTorch or similar frameworks (e.g Tensorflow) – demonstrates strong understanding of neural networks and LLMs; familiar with frameworks widely used in Hugging Face models, LLaMA, and similar architectures Expertise in fine-tuning methodologies – including data collection More ❯

models. Pilot emerging technologies. Experience & Skills 2–4 years in production-level AI/ML delivery. Legal/professional services experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration More ❯

Strong software engineering skills, especially in Python. Experience building robust systems for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in More ❯

model training, and deployment techniques. 7+ years’ experience in applied ML, data science, or AI, including senior or leadership roles. Expert in Python, proficient with frameworks such as PyTorch, TensorFlow, FastAI, and experience with scikit-learn, MLflow, or ONNX. Solid engineering background—experienced in deploying and maintaining ML systems on Azure, including Azure Machine Learning, Azure Functions, Databricks, Docker More ❯

security , and performance optimization . Strong understanding of AI frameworks and scalable infrastructure . Preferred: Master’s or Ph.D. in a related field. Experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn). Prior experience with healthcare or biomedical data . Certification in data governance or architecture (CDMP, DAMA, TOGAF). More ❯

deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. 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. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with More ❯

mentorship and guidance. Desirable: Exposure to courses related to Artificial Intelligence, Machine Learning, or Natural Language Processing Familiarity with frameworks like Express.js, Flask, or NestJS Familiarity with libraries like TensorFlow, PyTorch, or scikit-learn Basic understanding of Amazon Web Services Culture: Coffee and snacks in the office Team socials Inclusive working environment, supporting all genders, sexualities, race, disability or More ❯

learning, (ideally pose estimation, biomechanics or human movement) Proven technical leadership experience, ideally with direct reports. Track record of deploying ML models into production environments. Hands-on skills with TensorFlow, PyTorch, OpenCV, and Python ML frameworks. Excellent communication skills and ability to work cross-functionally. Desirable MSc/PhD in Machine Learning, Computer Vision, or related field. Knowledge of More ❯

DevOps practices . Experience in front-office risk, trading, or analytics systems within financial markets. Desirable/Highly Valued Skills: Exposure to AI and machine learning frameworks (e.g. PyTorch, TensorFlow, or similar). Interest in AI-driven automation, predictive analytics , and intelligent risk modelling . Experience with Rust , WebAssembly , or cross-runtime architectures . Solid grounding in data pipelines More ❯

especially for reinforcement learning or transformer based architectures • Hands on experience building and maintaining Frontend applications - React, Typescript • Strong programming background in Python and or relevant frameworks such as TensorFlow, PyTorch or Hugging Face • Fluent in cloud native development, containerisation, orchestration (for example Docker or Kubernetes) and CI/CD • Exceptional problem solver with an entrepreneurial mindset who is More ❯

agency, consultancy, or fast-paced business. Strong programming skills in Python, with experience building automation workflows, APIs, and data pipelines. Exposure to AI/ML frameworks (e.g. OpenAI, LangChain, TensorFlow, PyTorch). Solid knowledge of SQL and data warehousing concepts. Demonstrated experience with cloud platforms ( GCP & Azure preferred). Strong understanding of data modelling, transformation, and orchestration (e.g. dbt More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision-making and architecture ownership 🗣️ Excellent communicator — able More ❯

in you: Strong experience in applied ML or AI engineering, ideally with full-stack or backend development background Proficiency in Python and experience with frameworks such as PyTorch or TensorFlow Experience deploying ML models into production Familiarity with MLOps tools and cloud environments (AWS, GCP, or Azure) A genuine interest in using AI to solve real-world problems What More ❯