1 to 25 of 575 Machine Learning Jobs in the City of London

Hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base. The role is to define and set up a greenfield standardized MLOps framework for capital markets and set up all … for Capital markets. The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics. As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including … data scientists, quants, risk managers, traders, and other tech-savvy users. Core Responsibilities: Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks. Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle. Collaborate More ❯

Hands-on Machine Learning Operations (MLOps) Lead. This role will be pivotal in building out a greenfield framework for the deployment and management of scalable AI/ML solutions, specifically for the front and Middle Office user base. The role is to define and set up a greenfield standardized MLOps framework for capital markets and set up all … for Capital markets. The core platform is built on Azure Databricks Lakehouse, consolidating data from various front and Middle Office systems to support BI, MI, and advanced AI/ML analytics. As a lead, you will shape the MLOps framework and establish best practices for deploying and managing AI/ML solutions for a diverse and dynamic user base, including … data scientists, quants, risk managers, traders, and other tech-savvy users. Core Responsibilities: Lead the development of AI/ML CI/CD pipelines and frameworks for supporting AI/ML and Data Science solutions on Azure Databricks. Define and implement best practices for DataOps, DevOps, ModelOps, and LLMOps to standardize and accelerate the AI/ML life cycle. Collaborate More ❯

on efficiency, adaptability, and security . Algorithm & Model Development Develop and optimize AI algorithms for predictive analytics, recommendation engines, and automation in professional services. Apply machine learning (ML) and deep learning (DL) techniques to enhance decision-making and business intelligence. Data Engineering & Integration Architect robust data pipelines to support AI model training and inference. Implement automated data … inputs. Collaborate with data engineering teams to align AI solutions with real-world business applications. AI Model Training, Evaluation & Performance Optimization Train AI models using supervised, unsupervised, and reinforcement learning techniques , refining them based on business insights . Define model performance metrics to ensure AI solutions deliver tangible value. Real-Time AI Applications & System Integration Work alongside software engineers … and collaboration skills in cross-functional teams . Preferred Skills High-Performance Computing (HPC) and AI workloads for large-scale enterprise solutions. NVIDIA CUDA, cuDNN, TensorRT experience for deep learning acceleration. Big Data platforms (Hadoop, Spark) for AI-driven analytics in professional services. Pls share CV at payal.c@hcltech.com More ❯

best practices across the development lifecycle. Architecture & Design: Oversee system architecture decisions, ensuring alignment with business goals and scalability requirements. Mentorship: Mentor and guide junior developers, fostering a collaborative learning environment. API Development: Design and build RESTful API endpoints using NodeJS and Express, including detailed API documentation. Database Management: Design, optimize, and maintain complex SQL data models, ensuring efficient … Experience with AWS cloud services, Terraform, Docker, Kubernetes Agile/DevOps: Experience with Agile methodologies, CI/CD pipelines, and project management tools (Jira, Confluence, Bitbucket). AI/ML: Exposure to AI/ML projects or data analytics. Benefits and Perks Our comprehensive offering is designed around flexibility, well-being, and continuous growth, ensuring that you have the support More ❯

evaluation, performance tuning, and A/B testing methodologies Continuously monitor model behaviour post-deployment, addressing drift, feedback loops, and retraining strategies Contribute to and influence architectural decisions regarding ML systems and tooling (e.g., feature stores, orchestration frameworks, vector databases) Lead technical discussions, code reviews, and mentoring sessions for junior and mid-level data scientists Lead R&D initiatives by … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 5+ years hands on experience in data science or ML role with a strong focus on building and deploying production systems Deep technical expertise in machine learning, including supervised/unsupervised learning, NLP, and/or deep … learning Experience with large language models (LLMs), transformers, and modern NLP techniques (e.g., fine-tuning, embeddings, prompt engineering) Proven track record in designing, scaling, and maintaining ML systems in production (cloud-native solutions preferred – e.g., Azure, AWS, GCP) Excellent problem-solving skills and a passion for innovation and continuous learning Strong Python programming skills to write clean, modular More ❯

continuous years, and unspent criminal record check (known as Disclosure and Barring Service) Your Role We are looking for people with strong technical knowledge in areas such as machine learning, GenAI, computer vision, and data science, combined with solid solution architecture and software engineering skills, that will allow us to design and build solutions which can be deployed … your working reality. We have built an inclusive and welcoming environment, for everyone. Your Skills and Experience Capabilities in a range of AI techniques (e.g. supervised and un-supervised machine learning techniques, GenAI, deep learning, graph data analytics, statistical analysis, time series, geospatial, NLP, sentiment analysis, pattern detection, etc.). Strong communication skills - able to compellingly present … organisations, through e.g. the RFI/RFP process, as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools More ❯

Engineering Researcher' A UK based 'Enterprise' Artificial Intelligence organisation, focussing on helping accelerate their clients journey towards becoming 'AI-Optimal' - starting with significantly enhancing its abilities in leveraging AI & machine intelligence to outperform traditional competition. The firm builds upon its rapidly expanding research team of exceptional PhD computer scientists, software engineers, mathematicians & physicists, to use a unique multi-disciplinary … mathematical models − Ability to scale up algorithms to production Key Proposition: - This role offers the opportunity to be part of creating world-class engineered solutions within Artificial Intelligence/Machine Learning, with a steep learning curve and an unmatched research experience. Time Commitments: 100% (average 40 hours per week More ❯

applicants. Applying through Talent Hero gives you access to global opportunities without navigating the typical hiring grind. Youll work alongside US product, data, and engineering teams to build scalable ML pipelines and turn advanced algorithms into business value. We are looking for Machine Learning Engineers who are technically sharp, production-minded, and excited to push the boundaries of … learning models to solve complex business problems Develop scalable data pipelines for training, testing, and deploying models Collaborate with data scientists, product teams, and software engineers to integrate ML into production Optimize models for speed, accuracy, and efficiency in real-time environments Monitor model performance and implement feedback loops and retraining mechanisms Conduct experiments using A/B testing … and statistical analysis to validate approaches Document ML systems and provide support for ongoing performance tuning Use tools like Python, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, MLflow, Docker, SQL , and others Requirements Minimum Bachelors degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine Learning Engineer or in a similar More ❯

routines to clean, normalize, and aggregate data. Apply data processing techniques to handle complex data structures, handle missing or inconsistent data, and prepare the data for analysis, reporting, or machine learning tasks. Implement data de-identification/data masking in line with company standards. Monitor data pipelines and data systems to detect and resolve issues promptly. Develop monitoring More ❯

Senior AI/ML Engineer Location: London (2 Days in Office) Type: Permanent, Full-time About the Role An established tech company is building out its next generation of intelligent software products and is looking for a highly experienced Staff-level AI/ML Engineer to lead hands-on development of machine learning systems. This is a deeply … building production-grade AI tools from the ground up, this role offers the opportunity to shape something new in a growing, fast-paced environment. Key Responsibilities End-to-End ML Development Own the full lifecycle of machine learning initiatives — from idea to deployment and monitoring. Hands-On System Design Architect scalable, reliable ML pipelines and APIs, leveraging cloud … discussions, and knowledge sharing. Scalability & Reliability Solve practical challenges like data quality, explainability, and robust infrastructure for ML. What You’ll Bring 7+ years of hands-on experience building ML/AI systems in production. 3+ years in a senior technical contributor or team lead role. Advanced Python skills with exposure to common ML frameworks and data libraries. Solid experience More ❯

TLS, HTTPS, OAuth2, OIDC, SAML, JWT Languages - Python/Node.js/Golang Development – REST API/Microservices Desirable Skills: Multi-Cloud Knowledge/Experience - Azure/AWS. AI/ML – Vertex AI. Engagement with major blue-chip clients/financial organisations Certification GCP Professional Certification – Associate Engineer, Data, DevOps, Developer. More ❯

London, England, United Kingdom 1 week ago Business Data Architect – Keying and Linking Senior Software Engineer, Robotics & Microscope Control London, England, United Kingdom 3 weeks ago Senior AI/ML Engineer (Data Science & Software Focus) London, England, United Kingdom 2 weeks ago City Of London, England, United Kingdom 1 month ago London, England, United Kingdom 1 month ago London, England More ❯

a highly skilled and experienced AI Engineer to join their growing team. In this role, you will play a crucial part in developing and deploying cutting-edge AI/ML solutions within the financial services domain. You will work closely with the Founders and team to build the world's leading AI Agents for the financial services sector. Responsibilities: ● Design … develop, and deploy high-quality AI/ML capabilities. ● Research and evaluate new AI/ML algorithms and technologies. ● Collaborate with data scientists to prepare and engineer high-quality datasets for model training and evaluation. ● Develop and maintain robust and scalable machine learning pipelines. ● Conduct rigorous model validation and performance monitoring. ● Ensure the ethical and responsible use of … AI/ML technologies. ● Stay abreast of the latest advancements in AI/ML research and industry best practices. ● Contribute to the development of best practices for AI/ML development within the organization. Qualifications: ● 7+ years of professional experience in AI/ML engineering. ● Proven experience in working with financial data and developing AI/ML solutions for financial More ❯

sales enablement use cases. • Collaborate with retail clients to assess current infrastructure and define scalable cloud transformation strategies. • Lead the development of cloud-native microservices, event-driven systems, and ML pipelines using GCP tools. • Ensure solutions are secure, compliant, and aligned with retail industry standards and best practices. • Conduct architecture reviews, technical workshops, and hands-on engagements with customer engineering … or related field. • 10+ years of experience in cloud architecture/solution engineering, including at least 3 years in the retail industry. • 5+ years of experience in AI/ML engineering, with at least 2+ years specifically focused on Generative AI (LLMs, diffusion models, etc.). • Extensive experience designing GCP-based architectures leveraging services such as Vertex AI, BigQuery, Dataflow … or custom agent orchestration solutions). • Strong understanding of retail data ecosystems, POS integration, and customer engagement analytics. • Strong hands-on experience with Google Cloud Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). More ❯

quantitative research firm that continues to push the boundaries of advanced modelling — from algorithmic trading to factor modelling and other cutting-edge applications. Quant firms have leveraged AI and ML for years, but the increasing complexity and scale of global markets demand a more comprehensive, integrated approach. At AGITProp, we harness the latest insights from foundation and large language models … in the development and application of Large Language Models (LLMs), to join our growing team. This role blends research and engineering expertise, requiring a deep understanding of AI/ML principles, strong programming skills, and the ability to contribute to cutting-edge research while also building and deploying practical solutions. Experience in the financial services industry is highly desirable. The … novel architectures, training processes, and applications within the financial domain. Collaborate with portfolio managers, quants, traders, and engineers to understand business needs and translate them into effective AI/ML solutions. Build and maintain efficient, scalable, and reliable AI infrastructure, tools, and pipelines to support the development and deployment of machine learning models. Stay current with the latest More ❯

influencer & creative strategies and maximize their marketing towards optimal growth. In this role, you will be responsible for combining these otherwise disconnected datasets, and with the help of advanced machine learning, NLP & Computer Vision techniques, help uncover new consumer insights allowing our clients to gain knowledge and insights on consumer behaviour. You will play a key role in … Computer Science; Masters preferred. · 4+ years of experience in using Python to prepare, aggregate, or transform data (both structured and unstructured) for analysis · 4+ years of experience in applying ML/statistical methodologies on large datasets of respondent level, log file, or transactional level · Ambitious and open to learning many more ML and statistical methods, under mentorship of some … including unit testing and documentation · Proven experience building NLP & Computer Vision products with an engaged customer base · Experience researching and implementing latest scientific literature on NLP/CV and ML · Experience building prototypes and experiments to validate technical ideas · Extensive knowledge of open-source NLP & CV libraries · Skilled at explaining the technical subject matter to non-technical audiences (in English More ❯

leader in smart energy optimisation and predictive systems . As they continue to expand their AI capabilities, they’re seeking a Machine Learning Engineer to help productionise ML models and deliver real-time insights across their energy analytics platforms. Key Responsibilities: Develop, deploy, and monitor robust ML systems for energy usage prediction and optimisation Work on large-scale … time-series datasets to improve model accuracy and stability Collaborate with Data Scientists and DevOps to build end-to-end ML pipelines Contribute to model governance, MLOps, and performance monitoring frameworks Participate in code reviews, design discussions, and performance tuning Requirements: 3+ years of experience in a Machine Learning Engineer or similar role Proficiency in Python , ML frameworks … TensorFlow, PyTorch), and deployment tools (Docker, MLflow, etc.) Experience building scalable ML pipelines in cloud environments (AWS, GCP or Azure) Familiarity with energy systems, smart metering, or IoT data is a significant bonus Bachelor’s or Master’s degree in Computer Science, Engineering, Machine Learning, or a related discipline Strong problem-solving mindset and ability to work cross More ❯

tools such as Docker and Kubernetes. Familiarity with event-driven architecture and message brokers (e.g., Kafka, RabbitMQ). Knowledge of front-end performance optimisation and accessibility standards. Exposure to machine learning pipelines or data engineering workflows. Prior experience working in startup environments or high-growth technology companies. Benefits Hybrid working as standard 25 days annual leave plus bank More ❯

Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics: Databricks (AI & Machine Learning) Governance & Infrastructure: Centralised Data Catalogue & Access Control (Okta) Job Scheduling & Monitoring (AWS, Splunk) Agile Data Engineering with centralised code repositories BI Data Portal: Power BI However this coexists More ❯

to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership. Build strong relationships with a diverse range of stakeholders. Gain access to endless learning opportunities. Work closely with the range of teams within the business to bring products to life. The Role As a ServiceNow Solution Architect & PreSales Lead you will be in … knowledge of GenAI, predictive analytics, or automation workflows in enterprise environments. Familiarity with NLP frameworks (TensorFlow, PyTorch) and LLM fine-tuning techniques. ITIL certification and/or AI/ML certifications (AWS, Google Cloud). Experience with implementing scripted web services in ServiceNow, Java, and CMDB or asset integrations in ServiceNow. Knowledge of SAML, Active Directory, or LDAP. ServiceNow developer More ❯

onsite) - Flexible Salary: £45,000 DOE + Benefits Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) Engineer to join one our offices with hybrid or remote UK working. This is an exciting role and would most likely suit someone with previous experience in a similar role … where they have gained knowledge and experience of designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. You must have good technical knowledge of Phyton, SQL, CI/CD and familiar with Power BI. A FTSE 250 company, they combine expertise and insight with advanced technology and analytics to address … the analytics team and non-technical stakeholders. Your profile Essential Criteria Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

solutions. Act as a trusted expert on GCP data and AI solutions, both internally and with client stakeholders Design and deliver scalable architectures across data lakes, pipelines, AI/ML models, and real-time analytics Work in collaboration with Google Cloud teams, ensuring alignment to best practices and cutting-edge services Build reusable assets, accelerators, and frameworks to drive project More ❯

Staff AI/ML Engineer Location: London (Hybrid – 2 days/week in the office) Type: Permanent, Full-time About the Role An established tech company is building out its next generation of intelligent software products and is looking for a highly experienced Staff-level AI/ML Engineer to lead hands-on development of machine learning systems. … building production-grade AI tools from the ground up, this role offers the opportunity to shape something new in a growing, fast-paced environment. Key Responsibilities End-to-End ML Development Own the full lifecycle of machine learning initiatives — from idea to deployment and monitoring. Hands-On System Design Architect scalable, reliable ML pipelines and APIs, leveraging cloud … discussions, and knowledge sharing. Scalability & Reliability Solve practical challenges like data quality, explainability, and robust infrastructure for ML. What You’ll Bring 7+ years of hands-on experience building ML/AI systems in production. 3+ years in a senior technical contributor or team lead role. Advanced Python skills with exposure to common ML frameworks and data libraries. Solid experience More ❯

Team: Machine Learning Location: London (Liverpool Street) Employment Type: Full-time and Permanent Remuneration: £60–70k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Microsoft, Bloomberg and Goldman Sachs. We are backed by … develop methodologies and metrics to better understand the underlying quality, structure and distribution of training data. Architect training data validation, integrity and safety mechanisms for state-of-the-art ML models. Co-hire your future colleagues. Work closely with the founding team and contribute towards best practices, standards, and culture of the company. What we are looking for: Back-end … checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you. Nice to have: Machine Learning: Experience in generative models, LLMs, multi-modal models and Deep Learning more generally. Open-source: Contributions to and experience in open-source projects. Front-end: Experience More ❯

Team: Machine Learning Location: London (Liverpool Street) Employment Type: Full-time and Permanent Remuneration: £90–120k Base Salary + Discretionary Bonus + Equity We are a stealth-mode AI laboratory researching and developing Machine Learning models. The founding team consists of Cambridge graduates and former engineers at Microsoft, Bloomberg and Goldman Sachs. We are backed by … develop methodologies and metrics to better understand the underlying quality, structure and distribution of training data. Architect training data validation, integrity and safety mechanisms for state-of-the-art ML models. Be given a high degree of autonomy and ownership over your work. Co-hire your future colleagues. Work closely with the founding team and contribute towards best practices, standards … checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you. Nice to have: Machine Learning: Experience in generative models, LLMs, multi-modal models and Deep Learning more generally. Open-source: Contributions to and experience in open-source projects. Front-end: Experience More ❯