151 to 175 of 216 PyTorch Jobs in the UK

with RAG (retrieval-augmented generation) and GraphRAG a big plus Experience with building and deploying software on GitHub, PyPI, Anaconda Cloud, and Docker Hub, as well as use of Pytorch lightning, Git, test-driven design. Knowledge of parallel computing technologies, such as NVIDIA's CUDA platform, OpenCL, and OpenMPI. The salary range for Cambridge, UK: - Senior Scientist I, Computational Biology More ❯

Artificial Intelligence, Machine Learning, or a related scientific field, or equivalent industry experience. Strong programming skills, especially in Python, with hands-on experience using deep learning frameworks such as PyTorch or similar libraries. Proven experience applying classical and deep learning algorithms to biological problems, ideally in domains such as RNA design, optimization, and molecular modeling. Strong foundation in biology, biochemistry More ❯

efficiency at scale. These are powered by the AWS Neuron Software Development Kit (SDK), which includes a deep learning compiler, runtime, and native integration with popular ML frameworks like PyTorch, TensorFlow, and MXNet. Customers such as Snap, Autodesk, Amazon Alexa, and Amazon Rekognition are already benefiting from this technology at scale - and we're just getting started. The Opportunity - Tel More ❯

pipelines, and you're comfortable taking a feature from concept to deployment. Machine Learning Engineering & Research: A comprehensive background in machine learning, with deep experience in ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face) and a strong grasp of the underlying theory behind the models and techniques you use. Bonus Points: Experience with modern LLM orchestration frameworks (e.g., LangChain, LlamaIndex, DSPy More ❯

design and verification roles Linux - Essential for systems-level work Git, CI/CD tools (e.g. YAML, Terraform) - Common in DevOps and infrastructure roles Machine Learning Frameworks (e.g. TensorFlow, PyTorch) - Important for AI/ML roles Not every role requires all of these, but familiarity with at least one programming language (like Python or C++) and a collaborative toolset (e.g. More ❯

one or more Data Science or AI domains Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Experience with AI governance and responsible AI practices Understanding of public sector data requirements and compliance Outstanding More ❯

your tech lead and colleagues from the wider Data Science chapter at Lyst. We work mainly in Python using all the standard ML toolkits and frameworks (e.g. SKLearn, Tensorflow, Pytorch), and run our ML code in the AWS environment using Sagemaker where possible. We have a strong preference for clean, documented, well tested and reviewed code and have tooling and More ❯

Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able to design and implement MLOps solutions covering many different technologies. Desirable More ❯

benchmarks and user-defined success criteria. Essential Skills & Experience Proficient in Python, with hands-on experience using APIs and popular ML/AI frameworks such as Hugging Face, LangChain, PyTorch, or TensorFlow. Solid understanding of large language models (LLMs), prompt engineering, and vector database concepts. Proven ability to rapidly prototype, experiment, and iterate in agile or fast-moving environments. Familiarity More ❯

OCR, object detection, and cloud-native deployments , contributing to scalable, production-ready solutions in a collaborative, agile environment. What You'll Do: Build and deploy ML models using Transformers, PyTorch, YOLO, OpenCV , and more. Work with LLMs, image analysis, and object detection in real-world applications. Design and optimize APIs using FastAPI and integrate with external systems. Deploy scalable AI More ❯

For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI-driven industries. Independent, self-driven engineers who can own delivery without hand-holding. More ❯

For 5+ years’ experience in high-level engineering roles. Proven track record building ML research pipelines in complex technical environments. Experience in Python (and ideally C++) plus Kubernetes, Ray, PyTorch, Terraform, and cloud platforms (AWS, GCP, or Azure). Strong mathematical or statistical background. Background in AI-driven industries. Independent, self-driven engineers who can own delivery without hand-holding. More ❯

OCR, Object Detection and LLM analysis implementation LLM fine tuning Machine Learning & AI Libraries including: Transformers/Hugging Face Python expertise with an understanding of object-oriented programming Pandas, PyTorch, Numpy SQLAlchemy, Boto3 AWS - Lambda, S3, CDK API Development Design and implementation of AI/ML solutions Excellent communicator Strong stakeholder management Keen collaborator The above is not exhaustive. For More ❯

technical discussions with stakeholders, partners, and industry forums Required Qualifications 8+ years in AI/ML consulting, applied data science, or AI solution architecture Strong Python, ML frameworks (e.g. PyTorch, TensorFlow), and orchestration tools (e.g., MLflow, Ray, Kubeflow) Experience delivering enterprise AI projects — including LLMs, classification, recommendation, or optimization workloads Hands-on knowledge of GPU-based training and inferencing pipelines More ❯

inference stack Enhance system reliability and observability, and manage system outages Research and implement optimizations for LLM inference Qualifications Experience with ML systems and deep learning frameworks such as PyTorch, TensorFlow, ONNX Knowledge of LLM architectures and inference optimization techniques (e.g., batching, quantization) Experience deploying scalable, reliable, real-time model serving systems (Optional) GPU architecture understanding or CUDA programming experience More ❯

scale environments. NVIDIA Certified (Preferred). Required Skills Direct experience with GPU services, including resource provisioning, scaling, and optimization. Demonstrable expertise in GPU-accelerated software development (CUDA, OpenCL, TensorRT, PyTorch, TensorFlow, ONNX, etc.). Strong background in performance benchmarking, profiling (Nsight, nvprof, or similar tools), and workload tuning. Experience with Infrastructure as Code (Terraform, HELM Charts, or equivalent) for automated More ❯

track record of building and deploying LLM-powered applications in production , Deep experience applying large language models to complex, real-world problems , Strong proficiency in Python and ML frameworks (PyTorch, JAX, TensorFlow, Hugging Face Transformers) , Hands-on experience with advanced LLM techniques: RAG systems, chain-of-thought prompting, agentic tool use, and multi-agent coordination , Experience with distributed systems, cloud More ❯

Python, Ansible, or similar technologies. Experience leveraging AI/ML-driven tools for network performance optimization, anomaly detection, and predictive analytics. Understanding of AI frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn) and their application in network automation and monitoring. Experience with telemetry and observability frameworks (e.g., Prometheus, Grafana) for real-time network monitoring and troubleshooting. Experience : Minimum of More ❯

creativity, collaboration, and drive: Deep learning expertise with 2+ years in language generation. Experience with LLMs, neurosymbolic integration, and knowledge representation. Strong Python skills and experience with ML frameworks (PyTorch, HF, TensorFlow, JAX). Demonstrable track record of end-to-end applied research. Excellent communication skills; proven mentoring ability. Collaborative and proactive in fast-paced environments. Desirable: Experience with symbolic More ❯

experience, and c. 2+ years applying it to language generation, including working with Large Language Models, neurosymbolic integration and knowledge representation. Experience with Python and common ML Frameworks like Pytorch, HF Transformers, Tensorflow, JAX. Track record working as an independent contributor capable of end-to-end development with demonstrable experience in utilising and deploying transformer models. Deep knowledge of machine More ❯

andinternationally. RequiredExperience Strongknowledgeofdatamodelling,machinelearning,and/oradvanceddataanalytics. Demonstrabletrackrecordofdeliveringdataanalyticsprojectsaspartofateam. Hands-onexperiencewithcollaborativesoftwaredevelopmentandversioncontrol(preferablyGit). FamiliaritywithAgile/SCRUMmethodologies. Exposuretopre-engagementactivitiessuchasprojectscoping,technicalfeasibilityanalysis,orprototypedevelopment. Comfortablecontributingtotechnicaldiscussionsandimplementingsolutionsdefinedbyprojectleads. DesirableExperience StrongPythonexpertise. ExperiencewithGNU/Linuxenvironments. FamiliaritywithkeydatascienceandMLframeworks(e.g.,scikit-learn,PyTorch,TensorFlow,XGBoost,HuggingFace). Experienceinnaturallanguageprocessing,tabulardataanalysis,orcomputervision. SQLproficiency. Exposuretocontainerisation(Docker,Kubernetes)andcloud-nativearchitectures. ExperiencewithCI/CD,automatedtesting,anditerativeproductdevelopment. Knowledgeofgraphdatabasesandgraphanalysis. Benefits Ourclientoffersanexcitingandsupportiveenvironmentwithastrongfocusonemployeewellbeingandcareerdevelopment.Benefitsinclude: 35daysannualleave(includingpublicholidays)plusupto10daysunpaidleave. Flexibleworkingarrangementsaroundcorehours. Privatehealthinsuranceandpensionscheme. Contributiontogymmembership. Ongoingprofessionaldevelopmentsupport(courses,certifications More ❯

with some C++). Experience in embedded systems and automation/control mechanisms. Track record of leading or mentoring software engineers. Exposure to AWS and AI/ML frameworks (PyTorch, TensorFlow, OpenCV) is a big plus. Flexible, solutions-focused mindset – comfortable in a start-up environment. Nice-to-haves: Microcontrollers (Raspberry Pi, Okdo, Tinker Edge R). Robotics, servo/ More ❯

software engineering background with direct experience in machine learning applications. Proven track record leading teams – balancing delivery with career growth and mentorship. Proficiency in modern ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn) and cloud platforms. Comfortable working across the full lifecycle: from research prototypes to production-scale systems. Excellent communication skills and a collaborative mindset. Why apply? This is an More ❯

finance experts to translate real-world workflows into AI agents. Key Requirements: Strong experience in NLP/LLM training and fine-tuning (transformers, embeddings, LoRA/PEFT).Proficiency with PyTorch/TensorFlow, Hugging Face ecosystem, and MLOps tooling. Experience working with financial or structured transactional data. Knowledge of data privacy and regulatory requirements in fintech (SOC2, PCI-DSS, GDPR). More ❯

will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle Strong object-oriented programming skills and experience working with Python, PyTorch and NumPy are desirable Experience in one or more advanced optimisation methods, modern ML techniques, HPC, profiling, model inference; you don't need to have all of the above Excellent More ❯