26 to 50 of 109 TensorFlow Jobs in the City of London

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 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 ❯

Strong software engineering skills, especially in Python. Experience building robust systems for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in More ❯

Strong software engineering skills, especially in Python. Experience building robust systems for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker and Kubernetes in 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 ❯

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 ❯

code reviews, architectural decision-making, and technical debt management Ability to establish coding standards and best practices across teams AI/ML Expertise Strong understanding of machine learning frameworks (TensorFlow, PyTorch, Scikit-learn) Experience with LLM integration (OpenAI, Anthropic, open-source models) Knowledge of RAG architectures, prompt engineering, and vector databases (Pinecone, Weaviate) Experience with MLOps tools and monitoring More ❯

security , and performance optimization . Strong understanding of AI frameworks and scalable infrastructure . Preferred: Master’s or Ph.D. in a related field. Experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn). Prior experience with healthcare or biomedical data . Certification in data governance or architecture (CDMP, DAMA, TOGAF). More ❯

security , and performance optimization . Strong understanding of AI frameworks and scalable infrastructure . Preferred: Master’s or Ph.D. in a related field. Experience with ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn). Prior experience with healthcare or biomedical data . Certification in data governance or architecture (CDMP, DAMA, TOGAF). More ❯

from 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 More ❯

deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with More ❯

from 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 More ❯

deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work cross-functionally with More ❯

Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to fintech or start-up environments. Mindset & Attributes: Positive, objective-focused, and collaborative. More ❯

Familiarity with message brokers (Kafka, SQS/SNS, RabbitMQ). Knowledge of real-time streaming (Kafka Streams, Apache Flink, etc.). Exposure to big-data or machine-learning frameworks (TensorFlow, PyTorch, Hugging Face, LangChain). Understanding of infrastructure and DevOps (Terraform, Ansible, AWS, Kubernetes). Exposure to fintech or start-up environments. Mindset & Attributes: Positive, objective-focused, and collaborative. More ❯

or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional More ❯

or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively in cross-functional More ❯

knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). Strong leadership in project delivery, architecture, and technical decision-making. Excellent communicator, able to simplify complex ideas for any audience. Strategic thinker with awareness of FS sector trends. More ❯

knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong leadership in project delivery, architecture, and technical decision-making. 💡Excellent communicator, able to simplify complex ideas for any audience. 📈Strategic thinker with awareness of FS sector trends. More ❯

DevOps practices . Experience in front-office risk, trading, or analytics systems within financial markets. Desirable/Highly Valued Skills: Exposure to AI and machine learning frameworks (e.g. PyTorch, TensorFlow, or similar). Interest in AI-driven automation, predictive analytics , and intelligent risk modelling . Experience with Rust , WebAssembly , or cross-runtime architectures . Solid grounding in data pipelines More ❯

DevOps practices . Experience in front-office risk, trading, or analytics systems within financial markets. Desirable/Highly Valued Skills: Exposure to AI and machine learning frameworks (e.g. PyTorch, TensorFlow, or similar). Interest in AI-driven automation, predictive analytics , and intelligent risk modelling . Experience with Rust , WebAssembly , or cross-runtime architectures . Solid grounding in data pipelines More ❯