26 to 50 of 96 PyTorch Jobs in England

OpenAI, Anthropic, Llama), prompt engineering, fine‐tuning/customization, and embedding‐based retrieval. Intermediate to expert proficiency in Python (NumPy, Pandas, SpaCy, scikit‐learn, PyTorch/TF2, Hugging Face Transformers). Understanding of ML & Deep Learning models, including architectures for NLP (transformers), GNNs, and multimodal systems. Solid understanding of database ...

Scrum practices and a strong Agile mindset.· Advanced proficiency in Python and its key data and ML libraries (NumPy, PySpark, Scikit learn, TensorFlow/PyTorch)· Working knowledge of generative AI models (e.g., ChatGPT, Claude), Databricks GenAI tooling (including embedding models), and modern data structures such as vector databases.· Strong expertise ...

world problems with measurable business impact Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production‐grade code, and a solid understanding of data engineering and MLOps principles ...

again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions ...

incubations or complex deep‐tech cross‐functional initiatives with measurable outcomes. Expertise in Python and deep experience with deep‐learning frameworks (e.g., Jax, TensorFlow, PyTorch) and state‐of‐the‐art ML techniques. Practical experience with modern AI paradigms such as world models, foundation models, multi‐modal language models, agent‐based ...

equivalent experience). 4+ years of industry experience, focusing on deep learning-based NLP applications. Strong proficiency in deep learning frameworks such as PyTorch or TensorFlow. Hands‐on experience with cloud platforms (e.g., AWS, Google Cloud). Ability to drive AI initiatives from research to production in a collaborative environment. ...

peers in ML infrastructure, model deployment, distributed compute, GPU optimization, and MLOps architecture. Willingness to learn new parts of the ML tech stack – Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and model serving frameworks. Fluency in life sciences or drug discovery is a plus. Working ...

Computer Science (or equivalent proven track record). 4 + years working on large‐scale ML codebases. Hands‐on with PyTorch, JAX or TensorFlow; comfortable with distributed training (DeepSpeed/FSDP/SLURM/K8s). Experience in deep learning, NLP or LLMs; bonus for CUDA or data‐pipeline chops. ...

experience, or an MS with significant industry or research experience in the field Extensive experience with machine learning and deep learning toolkits (e.g. TensorFlow, PyTorch, NumPy, Scikit‐Learn, Pandas) Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with ...

MLOps system architecture. Excitement to learn parts of our ML tech stack that you might not already know. Our current ML infrastructure includes: Python, PyTorch, Docker, Kubernetes, Ray, Weights & Biases, Prefect, BigQuery, Postgres, GCP, CUDA, and various model serving frameworks. Fluency in life sciences or drug discovery is a plus ...

tier conferences or journals. Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system. Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches ...

systems at scale, including model lifecycle security, data pipelines, and secure deployment.* Strong hands‐on experience with machine learning stacks, such as PyTorch, TensorFlow, MLflow, Kubeflow, or equivalent managed platforms (e.g. Vertex AI, Azure ML).* Solid understanding of cloud‐native and containerised architectures, including Kubernetes and serverless technologies.* Experience ...

tier conferences or journals. Strong proficiency in programming languages such as Python, C/C++, experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras and experience with ROS or robotic operational system. Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches ...

cloud resources for data analytics and ensuring seamless integration of data pipelines and analytics platforms. Skilled with cloud-based machine learning toolsets , such as PyTorch or equivalent ML frameworks, to leverage state-of-the-art cloud technologies for advanced analytical modelling." Understanding of CI/CD practices , including ...

inference (e.g., dynamic batching, flash attention, speculative decoding) Proven track record of developing and deploying models at scale Expertise in Python, ML frameworks (TensorFlow, PyTorch), and experience with cloud platforms Strong familiarity with MLOps principles, CI/CD pipelines, and containerization (Docker, Kubernetes) With preferred backgrounds covering some ...

prediction market platforms (Polymarket, Manifold, etc.) Quantitative background in maths, statistics, or probability theory ML experience including random forests, regression models, scikit-learn, and PyTorch AWS infrastructure experience deploying containerised applications and managing cloud environments (EC2, Lambda, RDS) Open-source contributions to AI or crypto projects Compensation Salary ...

Python, C++, or similar Experience with optimization, reinforcement learning, and/or large language models (LLMs) Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch, JAX) Experience with scalable system design and deployment in research or production environments Exposure to chip design or applied AI research ...

Extensive experience with Python programming Commercial Machine Learning experience Experience working in Natural Language Processing (NLP) Experience training machine learning models using Tensorflow and PyTorch Experience working with search databases (e.g. Elasticsearch, Opensearch, etc.) Experience with cloud service providers (e.g. AWS) Willing to work 3 days per week onsite ...

documentation as we grow What we're looking for - * Solid experience working with AI/ML frameworks (e.g. LangChain, OpenAI API, Hugging Face, TensorFlow, PyTorch) * Comfortable writing production-ready code - Python particularly valued * Understanding of LLMs, prompt engineering, RAG pipelines or similar AI architectures * Ability to communicate technical ideas clearly ...

technical leadership Deep expertise in a relevant technical domain such as ML systems, data pipelines, backend engineering, or cloud infrastructure Hands‐on experience with PyTorch, TensorFlow, or similar ML frameworks Strong understanding of scalable APIs, cloud‐native systems, and modern engineering practices Experience creating Proof of Concepts and evaluating technical ...

/PhD or equivalent experience in Computer Science, Maths, Machine Learning, Data Science, or related field. Desirable: Exposure to machine learning frameworks such as PyTorch, JAX, Triton, TensorFlow Experience with distributed workload management systems such as Kubernetes, VLLM, Keras or MLOps pipelines Experience working with hardware simulators or emulators (e.g. ...

edge solutions. This role requires a proven record in delivering impactful ML/AI solutions and deep expertise in Python and modern frameworks like PyTorch and TensorFlow. The ideal candidate possesses strong communication skills and adaptability to thrive in fast-paced environments. Join a company backed by a major bank ...

integration from many sources. Python + ML/NLP stack High quality production code in Python . Libraries such as NetworkX , TensorFlow or PyTorch , NLTK, spaCy, Hugging Face, BERT , Pandas, NumPy, scikit learn . Graph based ML familiarity: link prediction, anomaly detection, traversal, community detection. NLP/NLU skills: entity ...

Overview AI/ML Engineers build, evaluate, and deploy machine‐learning systems at scale. The day‐to‐day work combines data preprocessing, model training (PyTorch, TensorFlow), evaluation against business or research metrics, and production deployment (FastAPI, Triton, Ray) with monitoring. The role increasingly overlaps with MLOps (model deployment, monitoring, retraining ...

Solid understanding of fundamentals of statistics, optimization and ML theory. Familiarity with popular deep learning architectures (transformers, CNN, autoencoders, etc.). Extensive experience with PyTorch, NumPy, Pandas. Hands‐on experience in implementing distributed/multi‐threaded/scalable applications (incl. frameworks such as Ray, Horovod, DeepSpeed, etc.). Able ...