51 to 75 of 99 TensorFlow Jobs in London

advances in temporal modeling and deep learning. Document methods and support reproducibility, validation, and publication where appropriate. Essential Requirements Strong programming and modeling skills in Python (NumPy, PyTorch or TensorFlow, SciPy, pandas). In-depth knowledge of machine learning for time-series, including RNNs, LSTMs, GRUs, transformers, attention mechanisms. Solid understanding of probabilistic models (HMMs, Bayesian inference, graphical models More ❯

propose innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in Python, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.) Expertise in 3D reconstruction and rendering Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker) Excellent problem-solving skills and ability to work cross More ❯

Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

experience in deep learning algorithms including the latest multimodal foundation models and generative AI frameworks' exploration, development, and implementation. Extensive experience with common machine learning Python frameworks such as TensorFlow and PyTorch; and Python libraries such as pandas, and computer vision libraries such as OpenCV. Experience in ONNX and TensorRT. Very comfortable working in Linux environment. Familiarity with software More ❯

deep learning and generative AI techniques, including implementing custom architectures, pretraining/fine-tuning generative models, building agentic workflows, and deploying solutions with real-world constraints. Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Preferred Qualifications Experience in building AI agents (based on RL, LLMs, etc.) Experience in building multi-agent simulation Background in Large Language Models/NLP More ❯

cross-platform integrations (e.g., Hyperscaler SDKs to Salesforce Flows). Prior exposure to conversational voice pipelines or multimodal integrations via hyperscaler services. Advanced AI/ML: Exposure to frameworks (TensorFlow, PyTorch), MLOps practices, and cloud AI platforms (e.g., Google Vertex AI, AWS Sagemaker). Hands-on work with Generative AI, Large Language Models (LLMs), agent-based frameworks, and prompt More ❯

and know how to translate those into robust, scalable digital environments. Experience with HPC, cloud platforms (AWS, Azure, GCP), containerisation (Docker, Singularity), and research software tools (MATLAB, R, Python, TensorFlow, NVivo) is essential. Familiarity with data governance, reproducibility frameworks, and AI ethics is highly desirable. More ❯

learning models, including Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile - you should be happy working with More ❯

team members, and collaborating closely with engineers, PMs and analysts to deliver measurable user and business impact. We work primarily in Python and SQL, with tools like Scikit-learn, Tensorflow, PyTorch and Pandas. Our ML stack runs on AWS and Sagemaker. We value clean, documented, well-tested and reviewed code-and have the tooling and culture to support this. More ❯

AI (recommendation systems, data mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master's (or equivalent experience) in Computer Science, AI, ML, or related field. Bonus points for: experience designing annotation schemas More ❯

data and machine learning systems Qualifications Strong understanding of machine learning principles, especially in the context of LLMs. Solid proficiency in Python, including machine learning packages like Jax/Tensorflow or PyTorch Experience with large-scale data infrastructure Strong verbal and written communication skills with the ability to work effectively across internal and external organisations and virtual teams. Would More ❯

Degree in Engineering, AI, Computer Science, Data Science, or a related field. Foundations in machine learning and computer vision. Strong Python skills with frameworks/tools such as PyTorch, TensorFlow, and OpenCV. Knowledge of version control (Git) and collaborative software practices. Problem-solving ability, adaptability, and a collaborative mindset. Wage: $35-47.50/hour (Intermediate), any hours worked More ❯

Degree in Engineering, AI, Computer Science, Data Science, or a related field. Foundations in machine learning and computer vision. Strong Python skills with frameworks/tools such as PyTorch, TensorFlow, and OpenCV. Knowledge of version control (Git) and collaborative software practices. Problem-solving ability, adaptability, and a collaborative mindset. Wage: $35-40/hour (Entry Level), any hours worked More ❯

background in machine learning, especially in generative models (e.g. GANs, VAEs, diffusion models) applied to chemical or materials domains. Proficient in programming and data analysis using Python, PyTorch or TensorFlow, and common cheminformatics or molecular simulation software. Excellent analytical, problem-solving, and communication skills-able to share complex concepts with technical and non-technical audiences. Proactive approach to autonomous More ❯

by 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 More ❯

scale AI systems. Expertise in Agentic AI, LLM-based architectures, NLP techniques, and generative AI models. Solid programming skills (Python preferred) and experience with ML frameworks such as PyTorch, TensorFlow, Hugging Face. Hands-on experience with prompt engineering, fine-tuning LLMs, and building multi-agent systems. Comfortable balancing strategic thinking with hands-on coding. If you want to lead More ❯

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 platforms More ❯

peers, and delivering high-impact work without direct management responsibilities. Proven experience mentoring and coaching colleagues. Strong Python skills and experience with ML frameworks such as PyTorch, HF Transformers, TensorFlow, or JAX. Track record of end-to-end applied research and deploying transformer models. Deep knowledge of machine learning fundamentals and cloud deployment. Excellent communication skills with the ability More ❯

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 ❯

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). Ability More ❯

frameworks and static code analysis tools (e.g. SonarQube) Agile methodologies (Scrum, Kanban, Lean) Desirable Skills Cloud platforms: AWS, Azure Containerisation: Docker, Kubernetes Machine Learning frameworks (AWS/Azure ML, TensorFlow) Relational, document, or graph databases Configuration management and deployment (Ansible) If you are a DV-clearable Senior Platform Engineer ready to make your expertise count in a challenging and More ❯

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 ❯

including 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 More ❯

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 reasoning More ❯