1 to 25 of 63 Remote Machine Learning Jobs in the City of London

Are you a Junior Machine Learning Engineer eager to turn messy, complex data into real-world intelligence? We’re looking for a curious and motivated Junior ML Engineer to join a hybrid-working team building cutting-edge data intelligence tools for the financial sector. You’ll spend part of your time collaborating in person with engineers and data … remotely — giving you the best of both worlds. You’ll be working on a platform that transforms unstructured private market data into actionable insights — learning how to design ML pipelines, fine-tune NLP models, and deploy solutions that really work in production. In this role, you’ll help train, test, and optimise models that can read, understand, and structure … world clients. What’s in it for you? 📄 AI That Matters – Work on models that make sense of unstructured financial documents and turn them into structured insights. ⚙ Hands-On ML Experience – Learn the full ML workflow — from cleaning data to deploying models and monitoring them in production. 📈 Mentorship & Growth – Work closely with experienced ML engineers who will guide your technical More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

processing. Responsibilities Develop, train, and optimise computer vision models for real world applications. Work with large datasets including images and video, ensuring data preprocessing, augmentation, and pipeline optimisation. Deploy ML models into production, ensuring scalability, efficiency, and reliability. Collaborate closely with data scientists, software engineers, and product teams to translate business needs into technical solutions. Stay up to date with … in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or … with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

processing. Responsibilities Develop, train, and optimise computer vision models for real world applications. Work with large datasets including images and video, ensuring data preprocessing, augmentation, and pipeline optimisation. Deploy ML models into production, ensuring scalability, efficiency, and reliability. Collaborate closely with data scientists, software engineers, and product teams to translate business needs into technical solutions. Stay up to date with … in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps tools (e.g., MLflow, Kubeflow, Docker, Kubernetes, or … with transformer-based vision models (ViT, CLIP, SAM). Familiarity with real-time inference and optimisation (ONNX, TensorRT). Previous work on video analytics, 3D vision, or multi-modal ML projects. More ❯

Science Manager to lead a core team responsible for critical models inside their product. We're in need of a leader to manage a team of excellent Data Scientists & Machine Learning Engineers as the business continues to grow & invest in itself. Someone who can work alongside key business stakeholders, driving the development of the main product through best … in-class Machine Learning solutions. Looking for a role that combines technical brilliance with broader strategy? Check out the summary below! 💰 Salary: £120,000 + bonus 💻 Benefits: Uncapped bonus structure, work from abroad etc. 🚀 Industry/Type of business: Fintech 🏠 Remote working: Hybrid, London 🧩 Interview process: 3 stages 📢 Reporting to: Senior Engineering Manager & C-Suite 👏 Company size … manage a team of 7 Machine Learning focused Data Scientists, including senior IC's and juniors Strategic skills in planning, roadmapping & team management The hands-on classic ML skills needed to be an effective over-the-shoulder manager driving team growth & expertise (80% hands-off, 20% hands-on) Python, SQL, Snowflake etc. The ability to engage a broad More ❯

decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. … of RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning … deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience More ❯

decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development. AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows. Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability. … of RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus. Experience & Knowledge Requirements Good knowledge of generative AI, machine learning … deep learning, natural language processing or other relevant AI fields. Proven track record of designing, developing, and deploying AI systems in production environments. Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers). Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph. Proven experience More ❯

data into valuable insights, supporting smarter, evidence-based decisions across the business. This is a fantastic opportunity for a recent graduate who’s passionate about data, problem-solving, and learning from experienced professionals in a collaborative environment. In this role, you’ll: 📊 Analyse datasets to uncover patterns, trends, and actionable insights 🧠 Apply statistical and machine learning techniques … Looking For: A degree in Data Science, Computer Science, Mathematics, Statistics, or a related field Familiarity with Python, R, or another programming language for data analysis Basic knowledge of machine learning concepts and statistical methods Strong analytical and problem-solving skills Good communication skills, with the ability to explain technical findings in simple terms Nice to Have: Experience More ❯

data into valuable insights, supporting smarter, evidence-based decisions across the business. This is a fantastic opportunity for a recent graduate who’s passionate about data, problem-solving, and learning from experienced professionals in a collaborative environment. In this role, you’ll: 📊 Analyse datasets to uncover patterns, trends, and actionable insights 🧠 Apply statistical and machine learning techniques … Looking For: A degree in Data Science, Computer Science, Mathematics, Statistics, or a related field Familiarity with Python, R, or another programming language for data analysis Basic knowledge of machine learning concepts and statistical methods Strong analytical and problem-solving skills Good communication skills, with the ability to explain technical findings in simple terms Nice to Have: Experience More ❯

methodology. Data Scientist tasks Build robust, containerised data science capabilities which are scalable across projects and products (Docker, Kubernetes) Collaborate with technical teams to write production-ready code, ensuring ML and AI models are deployable for your clients and projects. Collaborate with software engineers to design and deploy machine learning services that are accessible via APIs for use … in GUIs or direct access. Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the More ❯

learning and forecasting libraries. Work with product and data science management to develop key results for given product objectives. Establish scalable and efficient practices for data mining, ML model development, validation and inference. Building demand forecasting models Stay up-to-date on the most recent advances in AI and machine learning Requirements: MSc Degree in Computer More ❯

learning and forecasting libraries. Work with product and data science management to develop key results for given product objectives. Establish scalable and efficient practices for data mining, ML model development, validation and inference. Building demand forecasting models Stay up-to-date on the most recent advances in AI and machine learning Requirements: PhD Degree in Computer More ❯

a strong foundation in data science who is looking to make a meaningful impact in a high-performance, fast-paced environment. Key responsibilities Design, build, and maintain statistical or machine learning models to support sports forecasting and pricing across various markets. Extract actionable insights from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements … Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations … contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our company page, OTA More ❯

a strong foundation in data science who is looking to make a meaningful impact in a high-performance, fast-paced environment. Key responsibilities Design, build, and maintain statistical or machine learning models to support sports forecasting and pricing across various markets. Extract actionable insights from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements … Experience working with Python or R in a production or research setting. Strong experience using data wrangling tools (e.g. Pandas, NumPy, dplyr). Solid grasp of statistical modelling and machine learning, with hands-on use of libraries such as scikit-learn, xgboost, PyMC3, TensorFlow. Experience working with SQL and relational databases. Ability to explain model behaviour through visualisations … contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our company page, OTA More ❯

This hybrid role requires 2 days per week on-site and focuses on delivering advanced AI and data science solutions using cutting-edge technologies. Key Responsibilities: Design and implement machine learning models to solve complex business problems. Develop and deploy AI models using Python and Azure. Perform data analysis and build scalable solutions using SQL and other data … science tools. Collaborate with cross-functional teams to integrate AI into enterprise systems. Required Skills: Strong experience in Machine Learning , AI Modelling , and Data Science . Proficiency in Python , SQL , and Azure . Hands-on experience with modern AI and data science technologies. Ability to work in a fast-paced, collaborative environment. What's on Offer: £700/ More ❯

Job Title: Contract Deep Learning Engineer Location: London (Hybrid or On-site) Contract Type: 6–12 months (with potential extension) About the Role: We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world … computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model performance, and iterate based on results. Maintain … to knowledge sharing across the team. Stay up-to-date with the latest research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience More ❯

Job Title: Contract Deep Learning Engineer Location: London (Hybrid or On-site) Contract Type: 6–12 months (with potential extension) About the Role: We are seeking a highly skilled Deep Learning Engineer to join our team on a contract basis. You will be responsible for designing, developing, and deploying deep learning models to solve complex real-world … computer vision, natural language processing, and time-series analysis. Key Responsibilities: Design and implement deep learning models using frameworks such as PyTorch or TensorFlow. Collaborate with data scientists, ML engineers, and product teams to define model requirements and deployment strategies. Optimize model performance and scalability for production environments. Conduct experiments, evaluate model performance, and iterate based on results. Maintain … to knowledge sharing across the team. Stay up-to-date with the latest research and techniques in deep learning. Required Skills & Experience: Proven experience in developing and deploying deep learning models in production. Strong proficiency in Python and deep learning libraries (e.g., PyTorch, TensorFlow, Keras). Solid understanding of neural network architectures (CNNs, RNNs, Transformers, etc.). Experience More ❯

building the world’s first brain foundation models — large-scale AI systems designed to deeply understand, protect, and enhance the human brain. By generating our own data, developing novel machine learning approaches, and working closely with world-leading neuroscientists, the company aims to accelerate discoveries that transform how neurological diseases are treated and prevented. This is a rare … real-world insights from raw biological data. Key Responsibilities Design and implement distributed data pipelines for multi-omic, neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data … Flyte/Temporal) Hands-on cloud engineering experience (AWS, GCP, or Azure) Strong software engineering fundamentals, with a track record of writing maintainable, testable, and extensible code Familiarity with ML infrastructure and prior experience supporting ML teams in production environments Bioinformatics or biological data exposure (preferred, not required) — willingness to learn is essential Excellent communication skills and ability to collaborate More ❯

building the world’s first brain foundation models — large-scale AI systems designed to deeply understand, protect, and enhance the human brain. By generating our own data, developing novel machine learning approaches, and working closely with world-leading neuroscientists, the company aims to accelerate discoveries that transform how neurological diseases are treated and prevented. This is a rare … real-world insights from raw biological data. Key Responsibilities Design and implement distributed data pipelines for multi-omic, neuroscience, and clinical datasets Build a unified feature store to serve ML training and downstream biological analysis Develop scalable storage, ingestion, and validation systems with a focus on robustness, observability, and versioning Collaborate with ML researchers and biologists to translate raw data … Flyte/Temporal) Hands-on cloud engineering experience (AWS, GCP, or Azure) Strong software engineering fundamentals, with a track record of writing maintainable, testable, and extensible code Familiarity with ML infrastructure and prior experience supporting ML teams in production environments Bioinformatics or biological data exposure (preferred, not required) — willingness to learn is essential Excellent communication skills and ability to collaborate More ❯

get there): Cloud platforms (AWS, Azure) Containerisation (Docker, Kubernetes) Database systems (SQL, NoSQL, Graph) Configuration & deployment tools (Ansible) Exposure to Machine Learning frameworks (TensorFlow, AWS/Azure ML) The Package Up to £72,000 base salary Bonus scheme Hybrid working – London or Manchester hub Private healthcare & pension Career development pathways in a consulting-style environment Opportunities to contribute More ❯

get there): Cloud platforms (AWS, Azure) Containerisation (Docker, Kubernetes) Database systems (SQL, NoSQL, Graph) Configuration & deployment tools (Ansible) Exposure to Machine Learning frameworks (TensorFlow, AWS/Azure ML) The Package Up to £72,000 base salary Bonus scheme Hybrid working – London or Manchester hub Private healthcare & pension Career development pathways in a consulting-style environment Opportunities to contribute More ❯

ve assembled a world-class team from Cambridge, MIT, and Google across software, data science, theoretical physics, and computational geometry to build tools that transform large-scale engineering through machine learning and generative AI. They are now looking for a Senior Frontend Engineer with a passion for functional programming and elegant, performant user interfaces. The frontend stack includes … or related discipline) from a leading university, or equivalent practical experience Ability to commute to London once a week Nice-to-haves : OpenGL, Vulkan, Python, Tailwind CSS, AI/ML exposure This role is ideal for someone sharp, pragmatic, and passionate about engineering and design. You'll join a fast-paced startup culture that values learning, experimentation, and collaboration More ❯

Proficiency in Python and SQL for data processing and analysis Experience working with market data and its applications Familiarity with Databricks, Snowflake, and other modern data platforms Knowledge of machine learning and data science concepts is a plus This is a hybrid role based in London up to three days per week, with the rest of the week More ❯

touch ASAP as interviews are already taking place. Don't miss out! Key Skills: AWS, Data, Architecture, Data Engineering, Data Warehousing, Data Lakes, Databricks, Glue, Pyspark, Athena, Python, SQL, Machine Learning, London More ❯