1 to 25 of 187 Remote Machine Learning Jobs in Central 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 ❯

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 ❯

the way property is transacted globally. Ideal candidates will have: 5+ years in a leadership role such as Technical Lead or hands-on Engineering Manager, ideally within AI/ML, software development, or SaaS startups. Passionate about Generative AI and LLMs with a strong grasp of cutting-edge algorithms and technologies (e.g., NLP, computer vision, predictive analytics). Extensive experience More ❯

with. We encourage everyone to take responsibility and to be accountable. The Role 🧐 We're expanding our small and talented team and looking for a dedicated, proactive, and diligent ML Engineer to grow with us and enhance our ML and AI capabilities. This role will be a senior hire responsible for the software development and technical infrastructure needed to design … are full stack data professionals who independently manage projects across the complete spectrum, from raw data ingestion to deployment, monitoring, and optimization. While this role emphasizes data engineering and ML deployment, you will have the responsibility of managing projects with autonomy across the full data lifecycle. Responsibilities📝 As an ML Engineer at Un:hurd music, you'll be: MLOps and … Utilize PySpark for scalable processing of large datasets, implementing best practices for distributed computing. Optimize data storage and querying within a data lake environment to enhance accessibility and performance. ML R&D : Collaborate on model prototyping and development, identifying the most relevant and efficient solutions to the core problems that artists face. This involves deep research, hands-on experimentation, and 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

Quant Developer - AI/ML Greenfield Project Location: London, UK (Hybrid) Contract Type: 12-Month Contract (Inside IR35) Start Date: July 2025 About the Role We are partnering with a leading hedge fund embarking on a cutting-edge greenfield initiative to build a next-generation AI/ML-driven investment platform. This is a rare opportunity to join at inception … architecture, tooling, and models that will drive alpha generation and risk management for years to come. As a Quant Developer, you will work at the intersection of quantitative research, machine learning, and software engineering. You'll collaborate with quants, data scientists, and portfolio … managers to design and implement scalable systems for data ingestion, model training, and real-time signal deployment. Key Responsibilities Design and develop robust, high-performance systems for AI/ML model development and deployment. Collaborate with quantitative researchers to translate trading strategies into production-ready code. Build and maintain data pipelines for structured and unstructured financial data. Implement backtesting frameworks 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 ❯

of managing and growing high-performing data science teams. Excellent stakeholder management and communication skills – able to explain complex concepts in accessible language. Proficiency in tools such as Azure ML Studio , Databricks , AWS/SageMaker , Snowflake , and cloud-native platforms. Familiarity with CI/CD tools like Azure DevOps Pipelines or GitHub Actions . Comfortable working in Agile environments and More ❯

re building intelligent, data-driven products that empower smarter financial decisions. Title - Lead Data Scientist Hybrid - 3 days onsite Location - London Key Responsibilities Lead the development and deployment of machine learning models and advanced analytics solutions. Collaborate cross-functionally to identify and prioritize data science opportunities. Build and mentor a high-performing data science team. Establish best practices … for experimentation, model validation, and deployment. Communicate complex data insights to technical and non-technical stakeholders. Stay current with trends in data science, machine learning, and financial technologies. Requirements Bachelor’s degree in Computer Science, Data Science, Statistics, or a related field. 5–10 years of experience in data science, with at least 2 years in a leadership … depending on experience) Equity package. Flexible working hours and hybrid work environment. Opportunity to shape the future of finance with cutting-edge technology. Collaborative, mission-driven team culture. Learning and development budget to support your growth. More ❯

Databricks expertise. Data Quality & Monitoring: Implement comprehensive data quality checks, monitoring, and alerting mechanisms to ensure data integrity and reliability. MLOps Integration: Lay the groundwork for seamless integration with Machine Learning Operations (MLOps) capabilities for future AI initiatives. Documentation & Knowledge Transfer: Create comprehensive technical documentation and conduct knowledge transfer sessions to ensure long-term sustainability of the platform. More ❯

etc.) that flag when fresh weather guidance materially diverges from prior outlooks. Continuous Development and Improvement: Calibrate confidence metrics with historical data and measure their value to trading & risk learning models. Continuously improve these models based on … real-time data and feedback from trading activities. Model Communication: Explain uncertainty clearly, turning numbers into concise narratives and action-oriented alerts Broader Contributions: Build and refine statistical/ML models for short- to medium-term demand, renewables output, and other fundamental time series. Help design feature pipelines, scenario tools and model-performance dashboards used daily by traders and analysts. More ❯

Senior Data Engineer | Python, AWS, AI/ML | Data-Driven Insights Company My client is a leading provider of intelligence and data solutions to major players in the asset management industry. With a workforce of over 600 employees, they are currently expanding their tech and product offerings during a period of rapid growth. As a Senior Data Engineer, you will … a calendar full of social events and networking opportunities. What you will Bring: Proven excellence in ETL , scalable architectures , and automation . Experience in developing and deploying AI/ML pipelines. Excellent in Python , and good exposure to SQL , and both relational & NoSQL databases. Hands-on cloud experience (AWS or Azure or GCP) with IAC( Terraform )and CI/CD … Jenkins ). Experience in developing and deploying AI/ML pipelines . Familiarity with Airflow , Redshift , and dbt . What you will do: Architect, build, and optimise robust ETL processes for efficient data extraction, transformation, and loading. Develop an automation model and sophisticated data pipelines using Python, Airflow, Redshift, and more. Collaborate with data scientists to design, implement, and deploy More ❯

public sector and represent the company at industry events Skills Lead the delivery of high-impact data science deliveries across multiple client accounts and projects Design and implement advanced machine learning solutions and propositions using state-of-the-art techniques and best practices coupled with pragmatism to meet clients … needs. Deep expertise in one or more Data Science or AI domains Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible … Support business development through solution design and pre-sales activities Maintain high billable utilisation while delivering exceptional client value Contribute to Made Tech's thought leadership in AI/ML Guide clients in building robust MLOps practices and data-driven cultures Hiring and line-managing data scientists and analysts Security Clearance An increasing number of our customers are specifying a More ❯

Learning Engineer to support the development of a greenfield compliance platform focused on anti-money laundering (AML) and counter-terrorist financing (CTF). You’ll help design scalable ML infrastructure, build real-time monitoring systems, and explore the latest advancements in AI. Your Responsibilities: Contribute to a New ML-Driven Platform : Build advanced AML/CTF transaction monitoring modules … using both traditional statistical methods and modern ML techniques. Develop and deploy machine learning monitors using tools such as TensorFlow, OpenAI APIs, LangChain, Pytest, gRPC, and Python. Assist in implementing generative AI summarisation pipelines and agent communication protocols within a multi-agent system. Drive Deployment and ML Operations: Collaborate with DevOps to containerise and deploy monitors with automated … testing and evaluation tools. Support ML Ops development to track model health, detect drift/skew, and ensure model reliability in production. Focus on Scalability and Clean Code: Write clear, well-documented, and reusable code in line with engineering best practices. Help architect a scalable and resilient cloud-native platform (Azure) Maintain and improve data pipelines, ensuring data quality and More ❯

Azure Data Architects x 2 The Company: At Amber Labs, we are a cutting-edge UK and European technology consultancy that prioritises empowering autonomy, promoting experimentation, and facilitating rapid learning to provide exceptional value to our clients. Our company culture is centred around collaboration, where all colleagues, regardless of their role, work together to minimise risk and shorten delivery … skills, with the ability to liaise between clinicians, vendors, and technical teams. Desirable: Experience with hybrid data solutions, integrating on-premise and cloud data architectures. Background in data analytics, machine learning, and AI-driven insights for healthcare applications. Knowledge of NHS Digital initiatives, including Shared Care Records, the NHS App, and Population Health projects. Certifications in Azure Data More ❯

for a Machine Learning professional to join a high-performing team within a forward-thinking real estate technology business. What you'll be doing: Build and deploy ML/AI solutions for commercial real estate, including generative AI models, LLMs, and time series analysis. Process and analyse complex CRE datasets, engineer LLM prompts, evaluate outputs, and write production … ready Python code. Collaborate cross-functionally with product and engineering teams, translating business needs into ML tasks and contributing across the full development lifecycle. What we're looking for: Background & Experience: 3+ years in ML/AI with a Master’s (or higher) in a quantitative field such as Computer Science, Statistics, or Engineering. Technical Skills: Proficient in Python and … key ML libraries, with hands-on experience in LLMs, prompt engineering, data processing, and production-level code development. Mindset & Communication: Strong analytical thinking, scientific approach to problem-solving, and clear communication skills; familiarity with commercial real estate is a plus. Location: This is a remote-first role, with occasional travel to the Canary Wharf (London) office 1–2 times per More ❯

Data Scientist – Category Management (with ML/AI Focus) About the Role: Quest Search & Selection is working with a leading tech-driven eCommerce platform specializing in consumer goods and rapid delivery. Offering a wide product assortment; including groceries, household essentials, over-the-counter medicine, office supplies, and fresh food. The business leverages data and innovation at scale to drive customer … Create automated pipelines for monitoring performance of buying policies and flagging anomalies or risks in product lifecycle. Lead post-implementation reviews with insights into the performance of AI/ML systems and identify opportunities for further optimization. Set and tune dynamic targets for availability and expiry rates using continuous learning models. Guide and mentor a Data Analyst to support … ongoing analysis, data pipeline development, and dashboarding. Key Requirements: 4–6 years of experience in data science, analytics, or ML engineering , ideally in consumer products, retail tech, or supply chain. Solid understanding of supervised learning, time-series forecasting, clustering , and other core ML techniques. Strong experience with SQL and querying large, complex datasets. Proficiency in Python (Pandas, scikit-learn More ❯

+ 20% Bonus + £6,000 Car Allowance + 6% Pension +more Are you an experienced Data Science Manager with a passion for pricing strategy , machine learning , and commercial impact ? We're hiring on behalf of a major UK-based automotive group seeking a Data Science Manager to lead pricing analytics and shape the future of their data … processes to enable rapid innovation. What We're Looking For Essential Skills & Experience: Proven track record in pricing analytics , valuation modelling , or similar domains. Strong hands-on experience developing ML solutions in Python . Experience managing and growing high-performing data science teams. Ability to build and communicate complex solutions to stakeholders across different levels and disciplines. Proficiency working with … modern cloud-based tools (e.g., Azure ML , Databricks , Snowflake , SageMaker , etc.). Deep knowledge of machine learning techniques including predictive modelling, pattern recognition, and optimisation. Strong stakeholder management and product ownership skills. Experience with CI/CD tools such as Azure DevOps Pipelines or GitHub Actions. Desirable: Exposure to Marketing Data Science (e.g., Marketing Mix Modelling, Multi-Touch More ❯

BigQuery and PostgreSQL) proficiency and Python programming skills Experience with Google Cloud Platform Experience with big data warehouse systems (Google BigQuery, Apache Hive, etc) Hands on experience working with machine learning teams; understanding of the core concepts of model evaluation techniques and metrics, and suitable choices of their usage Experience working with data visualisation tools, particularly … Grafana Strong communication skills for client-facing interactions Collaborative mindset for cross-functional work Nice to Have Experience with image based machine learning Experience with AI/ML deployment workflows Experience communicating with non-technical stakeholders (client and internal) Startup experience This position offers significant growth potential in a fast-paced environment where you'll work with cutting More ❯

for leading GSI in the software engineering market AI Solution Architect to design and implement AI-driven agent solutions for the online commerce space. Deep understanding of AI/ML models, cloud computing, and scalable system architecture. This role requires expertise in architecting intelligent agents, optimizing cloud-based deployments, and integrating AI services into enterprise applications. Key Responsibilities: Architect and … ECS, etc.) to deploy scalable AI solutions. Implement Full Stack JavaScript (Node.js, React.js, Express, TypeScript, Next.js, etc.) applications to support AI-driven interfaces. Work closely with data scientists and ML engineers to integrate machine learning models into cloud-native applications. Ensure security, scalability, and reliability of AI agent solutions in production environments. Design event-driven and serverless architectures … governance. Required: 5+ years of experience in solution architecture with a focus on AI, APIs, and cloud technologies. Strong hands-on experience with AWS services related to AI/ML and serverless computing. Proficiency in JavaScript, TypeScript, Node.js, React.js, and Express.js for building full-stack applications. Experience with AI/ML frameworks such as TensorFlow, PyTorch, OpenAI API, or LangChain. More ❯

lead on building Python-based AI solutions and modern data-driven applications. Key Responsibilities: Design, build, and maintain scalable Python applications. Modernise and enhance legacy systems using AI/ML approaches. Develop APIs and data pipelines for both batch and real-time processing. Build, train, and deploy AI models with a focus on performance, accuracy, and scalability. Engineer AI-powered … in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. … Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant SDKs (e.g., boto3, confluent-kafka). Experience deploying ML models in production using REST APIs, microservices, and Docker containers. Understanding of NLP, LLMs, and prompt engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. More ❯