25 of 25 TensorFlow Jobs in the City of London

grow. What We’re Looking For: 🎓 A degree in Computer Science, Data Science, Artificial Intelligence, Mathematics, or a related field 🐍 Proficiency in Python and familiarity with libraries such as TensorFlow, PyTorch, or scikit-learn 🧩 Understanding of machine learning algorithms and statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to More ❯

.NET development and AI Required Skills & Qualifications: Strong experience in C#, .NET Framework, .NET Core/6/7, ASP.NET Experience with AI/ML frameworks such as: ML.NET TensorFlow/PyTorch (for integration with .NET) Azure Cognitive Services/OpenAI/AI APIs Knowledge of RESTful APIs , microservices, and cloud platforms (Azure, AWS, or GCP) Familiarity with SQL More ❯

in production. What We’re Looking For 3+ years of experience in Data Science. 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/ 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 ❯

writing simple scripts, and building custom scenarios to prove a point. Highly Desired: Direct experience with our specific AI domain (e.g., experience with LangChain for an LLM company, or TensorFlow/PyTorch for a computer vision company). Understanding of MLOps principles and the end-to-end machine learning lifecycle. Programming/scripting experience (e.g., Python, SQL) to manipulate 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 ❯

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 ❯

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 ❯

years in a leadership role. Proven experience delivering production-grade systems in Search, Recommender Systems , or Personalisation . Strong understanding of ML fundamentals and deep learning frameworks (e.g., PyTorch, TensorFlow, JAX). Hands-on experience with GenAI , including working with LLMs (e.g., OpenAI, Anthropic, HuggingFace models). Deep knowledge of MLOps, experimentation, and model evaluation techniques. Experience scaling ML 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 ❯

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 ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

to impactfully solve their problems. Deep understanding of machine learning theory. Strong coding skills in Python and hands on experience using at least one of the deep learning frameworks Tensorflow or PyTorch. Desirable Skills: Technical experience in uncertainty modelling, explainable machine learning techniques, out-of-distribution detection, life-long learning, and related fields. Technical experience with signal processing and More ❯

Key Skills & Experience: 5+ years of experience within AI/ML Engineer Strong background in AI/ML Engineering Python expertise Knowledge of ML libraries such a PyTorch or TensorFlow Cloud platform experience (AWS, Azure or GCP) Experience working in production environments, shipping and building products This role is a hybrid role with 2-days a week required in More ❯

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 ❯

of senior applied scientists Essential Skills: Formal training in machine learning and computer vision Coding experience in python Experience working with at least one deep learning framework (pytorch or tensorflow) A strong willingness to learn Highly collaborative mindset A strong interest for a product-centric organization Desirable Skills: Working knowledge of cloud computing (preferably AWS) and tools and technologies More ❯

equivalent experience in 3D graphics or ML systems. Strong in C Python, 3D graphics pipelines, inverse rendering, and geometry processing. Experience with GPU programming (OpenGL, CUDA, Vulkan), PyTorch/TensorFlow, and real-time engines (Unity/Unreal). Solid grasp of optimization, linear algebra, computer vision, and numerical methods. Skilled in multithreading, memory management, and profiling for high-performance More ❯

development. • Experience with parallel processing programming. • Understanding of standardization processes and standard-developing organizations (SDOs). Beneficial to have: • Knowledge of objective Visual Quality (VQ) assessment techniques. • Experience with TensorFlow, visual AI (e.g., media indexing), and/or multimodal Generative AI. • Experience in Intellectual Property development. • Experience presenting research findings at conferences and within video-centric forums. • Contribution to More ❯

moving, highly regulated industry. The Player You’re fluent in generative AI, from prompt engineering to deploying production-ready LLMs. You bring cloud-savvy skills, mastery of tools like TensorFlow or PyTorch, and a sharp eye for AI trends and ethics. You’re collaborative, curious, and ready to build intelligent systems that perform at scale. If you’re passionate More ❯

scalable user interactions Essential Qualifications: Experience with real-time protocols (eg. WebSockets gRPC, MQTT, SSE or similar) Experience with implementing on-device machine learning (eg. PyTorch Mobile, ML Kit, TensorFlow Lite) Strong understanding of Android performance: lifecycle, coroutines, memory, and threading Familiarity with edge-friendly architecture: offline-first, sync queues, reactive flows Comfort working in fast-paced, zero-legacy More ❯

on-device during live shopping experiences. Build robust evaluation pipelines that ensure on-device implementations mirror the performance of offline systems. Integrate models with mobile inference backends such as TensorFlow Lite, ONNX Runtime Mobile, MediaPipe or custom native models. Build and manage real-time on-device data stores for low-latency context and lookup. Collaborate with Research Scientists and … mobile or edge devices, ideally Android. Strong proficiency in Python and Java or Kotlin, with experience translating ML code between languages. Practical experience with mobile inference frameworks such as TensorFlow Lite, ONNX Runtime, or similar tools. Familiarity with GPU acceleration on mobile (e.g., GPU delegates, Vulkan) or ARM-based systems is a plus. A mindset that combines engineering rigour More ❯