1 to 25 of 35 Permanent PyTorch Jobs in Berkshire

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: 💰 Competitive Salary More ❯

natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience with modern engineering More ❯

presentations to client stakeholders; conduct demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex AI), MLOps/LLMOps tools (MLflow More ❯

re Looking For 2–5 years of experience in ML Engineering or MLOps. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow) and feature/data platforms More ❯

and implementing solutions defined by project leads. Desirable Experience Strong Python expertise. Experience with GNU/Linux environments. Familiarity with key data science and ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow, XGBoost, Hugging Face). Experience in natural language processing, tabular data analysis, or computer vision. SQL proficiency. Exposure to containerisation (Docker, Kubernetes) and cloud-native architectures. Experience with CI More ❯

managing ML in production. What we’re looking for Active SC Clearance Strong software engineering background with proficiency in Python. Experience deploying ML models built with frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers More ❯

structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively with stakeholders and More ❯

Kubernetes, MLflow, Weights & Biases]. Solid understanding of vector databases and their application in RAG systems. Strong communication and collaboration skills. Preferred Qualifications Experience with low-level ML frameworks [PyTorch, TensorFlow] for fine-tuning LLMs. Experience with speech recognition systems [e.g., Whisper] or computer vision models. Contributions to open-source AI projects. Experience with cloud platforms [AWS, GCP, Azure]. More ❯

impact solutions. Mentor engineers, lead code reviews, and promote engineering best practices. Required Skills & Experience: Substantial experience in AI/ML product development. Strong background in Python, TensorFlow or PyTorch, and cloud ML services (AWS, GCP, or Azure). Proven ability to build, tune, and deploy ML models into production. Experience developing and maintaining high-performance APIs and backend services. More ❯

and ability to present complex ideas clearly Nice-to-have Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Previous research publications or submitted papers Why Join Us Gain hands-on experience in state-of-the-art AI research with real-world applications Collaborate with a team of More ❯

skills, with the ability to present complex ideas clearly Preferred: Experience in optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) A strong publication record in top conferences (e.g., NeurIPS, ICML, ICLR, ACL) Why Join Us Work on groundbreaking AI research with real-world applications and a strong commitment to More ❯

position sits between the engineering and the investment team. You will wear multiple hats and leverage new AI and ML technologies. 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 (Tableau or similar More ❯

in Reinforcement 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 More ❯

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 comfortable with More ❯

complex technical concepts to both technical and non-technical audiences. Job requirements: Proven track record as a Machine Learning Scientist delivering models into production. Expertise with frameworks such as PyTorch, TensorFlow, or Transformers. Strong Python skills with clean, production-ready coding practices. Solid knowledge of data engineering and MLOps principles. Ability to lead end-to-end ML projects and mentor More ❯

research Requirements: PhD or equivalent experience in ML, AI, CS, physics, or mathematics Strong publication record (NeurIPS, ICML, ICLR, etc.) Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindse Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work More ❯

closely with investors and engineers to forecast key 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 (Tableau or similar More ❯

Working model : Hybrid (3 days/week in central London) Tech stack : Python, Docker, AWS (Lambda, Step Functions, Bedrock), CI/CD, LLM APIs Desired Skills and Experience Python PyTorch AWS Docker CI/CD More ❯

CNNs and RNNs as well as bleeding edge architectures such as state space models Excellent Python programming skills Expert in at least one popular machine learning framework such as Pytorch Knowledge of real-time audio signal processing and/or real-time machine learning Proven experience of applying and optimising AI/ML techniques and algorithms in a product-driven More ❯

of software development experience Proven track record of building and shipping full-stack products in fast-paced, product-driven teams Hands-on experience building production AI systems with Python, PyTorch, and LLMs (OpenAI, Anthropic, etc.), integrated into real user workflows Familiarity with MLOps tools and CI/CD for both traditional and ML-driven systems Strong backend and API development More ❯

complex real-world problems across domains such as computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model … research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Familiarity with MLOps More ❯

science, or a related field. Proven expertise in deep learning research and model development. Strong knowledge of mathematics (linear algebra, calculus, statistics). Experience with ML frameworks such as PyTorch, TensorFlow, or JAX. A passion for applying ML to real-world scientific challenges. Nice to have Experience working with biological or chemical data. Familiarity with large-scale deep learning, generative More ❯

including prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

enable engineers to design, manufacture, and operate advanced systems more efficiently than ever before. They’re looking for someone who: Has strong Python skills (NumPy, SciPy, Pandas, TensorFlow or PyTorch) Brings experience in data-driven modelling, probabilistic methods, and deep learning Enjoys working directly with customers and solving complex engineering problems Can build scalable data pipelines and deploy production-ready More ❯

we’re looking for 3+ years developing deep learning systems with shipped models or published research. Hands-on with Vision Language Models, LLMs or generative models. Strong Python + PyTorch/JAX skills (debugging, profiling, shipping). Passion for bridging the gap between simulation and reality. This is one of the most exciting and technically challenging roles I’ve see More ❯