1 to 25 of 192 Machine Learning Jobs in the City of London

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

access services quickly and safely. Our Applied Scientist team consists of about twenty machine learning scientists. The team is supported by an ML Ops team that provides state-of-the-art tooling (including AWS, Encord, Ray, PyTorch Lightning and Weights & Biases). The Applied Science team works closely … Have strong experience in machine learning and computer vision. Have a strong record of successfully delivering high-performance ML-driven products. Have a deep understanding of machine learning theory. Have strong coding skills in Python and PyTorch. Care about building fair and cutting-edge machine ...

Machine Learning Engineer, you’ll work closely with Data Scientists, Data Engineers and delivery teams to productionise models and build robust, scalable ML systems within client environments. This role is highly hands-on, with a strong focus on deployment, performance and reliability. Key Responsibilities Translating data science models … into scalable, production-ready machine learning solutions. Designing and building end-to-end ML pipelines, from data ingestion to deployment and monitoring. Collaborating with data engineers on data architecture, pipelines and feature stores. Working closely with data scientists to productionise models and improve performance. Deploying, monitoring and maintaining ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance. Experimentation: Design and analysis of A/B tests and offline experiments … full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance. Strong proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch). . Experience using ML Training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and Model Serving technologies (eg. Tensorflow Serving ...

applied artificial intelligence, solving complex real-world problems in national security and defence environments. The Role You will design, develop and deploy advanced ML models within secure environments, contributing across the full lifecycle from research through to production. Projects may include: Computer vision and pattern recognition systems Synthetic data generation … modelling Deep neural networks (DNNs) for real-world defence applications Simulation and AI-driven modelling environments Advanced research-led ML solutions You will collaborate with research scientists, software engineers and domain experts to translate cutting-edge techniques into deployable capability. Key Skills & Experience Proven experience working within the UK defence ...

Learning Engineer to join our growing team. This is an exciting opportunity for women who want to advance their career in AI/ML, work on meaningful projects, and thrive in a supportive, collaborative environment. What Youll Do: Design, develop, and deploy machine learning models using modern … stakeholders to turn ideas into impactful solutions. Optimize and deploy models with tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate ML solutions into production environments. Monitor and improve model ...

mission-driven technology company operating in the life sciences domain is seeking a Principal Scientist - hands-on with either ADMET or Structural Biology modelling, ML engineer to lead the technical direction for ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) modeling efforts within its drug discovery platform. The organisation enables collaborative … machine learning, computational chemistry, and applied research to advance foundational model applications in drug discovery. You'll be the technical authority on ML architecture, experimentation, and strategy, while focusing specifically on data security and privacy. You will also collaborateclosely with leadership and mentoring other engineers and researchers. While ...

Data scientist- Principal Data Scientist/Senior Machine Learning Scientist/AI/ML Solution Architect Key Responsibilities Lead end-to-end machine learning solution delivery for complex enterprise use cases Translate ambiguous business challenges into structured ML problem statements and solution architectures Design, develop … engineering teams to transition models into scalable production systems Mentor data scientists and uphold modelling standards, documentation, and reproducibility best practices Contribute to reusable ML frameworks, accelerators, and innovation initiatives Required Experience & Qualifications 15+ years of total professional experience , including 8+ years of hands-on experience in machine learning ...

machine learning models in production. Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products. Supporting the full ML lifecycle, from experimentation to deployment and optimisation. Applying best practices in data engineering and contributing to architectural decisions. Using modern MLOps tools and CI/… knowledge-sharing and continuous improvement. Technical Experience Were looking for experience in many of the following areas: Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn. Experience with frameworks such as TensorFlow, Keras, or PyTorch. Exposure to gradient boosting tools such as XGBoost, LightGBM ...

years’ commercial experience in Machine Learning Strong experience in Computer Vision (e.g. object detection, image classification, segmentation) Experience building, training and optimising ML models Python (NumPy, Pandas, scikit-learn) and frameworks such as TensorFlow or PyTorch Experience deploying models into production environments (cloud platforms, Docker, CI/… resided in the UK continuously for the last 5 years) These roles offer the opportunity to work on impactful, real-world projects where robust ML solutions are critical. If you’re exploring new contract opportunities and meet the above criteria, please apply or drop me a direct message. ...

solutions. Key Responsibilities: Design, build and deploy machine learning and AI solutions for enterprise clients Develop models using Python, PyTorch and modern ML frameworks Work with large datasets to train, evaluate and optimise models Implement and scale solutions on AWS (SageMaker, Bedrock, Lambda, etc.) Contribute to generative … Data Science roles Strong Python programming skills Hands-on experience with PyTorch Experience with Hugging Face transformers or similar frameworks Solid experience deploying ML solutions on AWS Understanding of MLOps, model deployment and performance optimisation Ability to work in a consultancy environment with multiple clients Desirable: Experience with LLMs ...

intersection of machine learning, product, and engineering, working closely with a world-class research team to turn advanced ML capabilities into a coherent, high-impact agent used on real-world problems. More specifically, you'll build the intelligence layer of their highly advanced agentic AI agent. … help design: The iterative interaction between the Agent and users The ML logic and decision workflows powering the Agent Reusable predictive pipelines that generalise across datasets Robust evaluation and model comparison frameworks This is a high-ownership role where you’ll shape core product architecture in a fast-moving environment. ...

Programmes We are supporting a specialist AI organisation delivering advanced machine learning capability into the defence sector. They require a Contract ML Engineer to support ongoing high-priority programmes. This is an outside IR35 engagement at £550 per day, suited to an experienced contractor who can operate independently … within secure environments. The Role You will work on the development and optimisation of advanced ML models, contributing to applied AI solutions across defence and national security projects. Key responsibilities include: Designing and implementing deep learning models Developing computer vision and pattern recognition systems Building and refining synthetic data ...

Senior Machine Learning Engineer — Ranking & Recommendations Tech Stack: Python, GCP, BigQuery, dbt, modern ML frameworks, LLMs, embeddings, RAG Salary: £110,000 – £130,000 plus 8% bonus Contract: Permanent, full-time Location: London, 3 days per week Sponsorship: Tier 2 sponsorship available We're looking for a Senior Machine Learning Engineer to be the first dedicated ML hire. You'll work alongside the Data Engineering team to design, build, and own the recommendations infrastructure from the ground up, while helping define the long-term ML strategy - establishing best practices for model development, experimentation, evaluation, and monitoring. ...

with large, complex datasets to support AI-driven products and insights 🧠 Assist with feature engineering, model experimentation, and performance optimisation ☁️ Contribute to data and ML pipelines in cloud-based environments 🗄 Work with structured and semi-structured data using SQL 🚀 Support the deployment and monitoring of models in production environments 🤝 Collaborate … years of experience in AI, machine learning, or software/data engineering (including internships, placements, or academic projects) 🐍 Strong Python skills for ML and data processing 🗄 Experience working with SQL and structured datasets ☁️ Familiarity with cloud platforms and modern data stacks 🧠 A solid understanding of machine learning ...

engineering environment. Required: Core experience Strong grounding in audio machine learning or applied signal processing Experience training and evaluating models using modern ML tooling Awareness of real-world acoustic challenges such as noise, reverberation, and variability Comfort working in a small, fast-moving engineering team Likely … + some industry experience Beneficial Edge or embedded ML optimisation Audio feature extraction or DSP knowledge Postgraduate study in a relevant technical discipline Experience with sensing, monitoring, or real-world data systems ...

this role! You'll help lead and implement the improvement of algorithms, optimising execution, usability, and package architecture of our ML Verification packages. Note that this is a Python code focused role, rather than a Data Science role, so Python programming skills are the priority, where as Machine Learning … systems we build are safe to use. To meet this need, we are developing advanced deep validation techniques and tools that allow AI/ML engineers world-wide to validate the robustness of their models, as well as repair the fragilities that they discover. By joining ...

client is looking for an experienced ML Infrastructure Engineer to support the deployment, optimisation and scaling of advanced machine learning models in production environments. This role sits at the intersection of research and engineering, focused on ensuring models are reliably transitioned from experimentation through to large-scale deployment. … improve deployment efficiency and platform scalability Evaluate and integrate third-party infrastructure and inference tooling where appropriate Requirements Proven experience deploying and maintaining ML inference systems in production environments Strong programming experience in Python and familiarity with modern machine learning frameworks Experience working with containerisation and orchestration technologies ...

someone who enjoys technical depth, variety, and ownership, and who is comfortable applying the right techniques to each problem - from statistical analysis through to machine learning and deep learning models. You’ll join a small, high-calibre team that values autonomy, flexibility and technical excellence. The environment … actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. Working with large, structured and unstructured datasets, combining ...

Machine Learning Engineer Full Time London - Hybrid Were partnering with a rapidly scaling PropTech SaaS business transforming how property … data is enriched, automated, and delivered across multi-tenant environments. Theyre now hiring a Machine Learning Engineerto help build intelligent, production-grade ML systems at the core of their platform click apply for full job details ...