976 to 1,000 of 1,175 Machine Learning Jobs

What We’re Looking For Strong experience as an AI/ML Engineer or Applied ML Engineer Deep hands-on knowledge of Google Cloud Platform (Vertex AI, BigQuery, Cloud Run, GKE, Pub/Sub) Proven track record building LLM, GenAI, or traditional ML solutions end-to-end Comfortable in startup … scale-up environments — fast-moving, iterative, delivery-focused Strong Python engineering experience Experience with MLOps, CI/CD, IaC, and productionising ML models Ability to work collaboratively with product, data, and engineering teams Contract Details Location: Hybrid London (2–3 days onsite) Start Date: ASAP Length: 6 months rolling ...

aligned to client needs: software programming, Java full stack development, Java/Python roles, DevOps engineering, and data roles spanning analytics, engineering, science, and ML/AI. Our primary focus remains Java/Full Stack/DevOps and Data/Engineering/Analytics/ML. SynergisticIT since 2010 has helped … build + deploy + collaborate + document + explain." That's especially true for Java full stack, DevOps, data engineering, and ML/AI. What roles are commonly in demand right now Laid-off candidates often do best targeting roles that map to consistent enterprise demand. The main lanes include ...

Role: AI/ML Computational Science Manager Location: Glasgow Salary: Competitive salary and package dependent on experience Career Level: Manager (CL7) Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these … industries, including Financial Services, Resources, Products, Communications and Health & Public Services. In our team, you will: How to help clients to use AI/ML technologies to solve business challenges How to design, develop, deploy, and run high quality AI/ML solutions across a range of industries with varying ...

Role: AI/ML Computational Science Manager Location: London Salary: Competitive salary and package dependent on experience Career Level: Manager (CL7) Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across all of these … industries, including Financial Services, Resources, Products, Communications and Health & Public Services. In our team, you will: How to help clients to use AI/ML technologies to solve business challenges How to design, develop, deploy, and run high quality AI/ML solutions across a range of industries with varying ...

emerging AI technologies and apply them pragmatically (not experimentally) • Own the agency-wide experimentation roadmap • Design structured tests with clear hypotheses, success criteria and learning outcomes • Introduce advanced testing methodologies (e.g. multi-armed bandits, automation-led testing) • Ensure learnings are embedded back into channel strategies, not left as theory … platform mechanics and APIs (Google, Meta, etc.) • Commercial mindset - able to balance statistical rigour with business reality Desirable • Experience implementing AI or ML models in marketing environments • Familiarity with automation tools, cloud data platforms, and LLMs for analysis • Agency experience or working in fast-paced, client-facing environments • Experience designing ...

Head of Data & Analytics, you will design, develop and maintain secure, high-quality data pipelines that enable trusted reporting, analytics, and future AI/ML development. This is a rare opportunity to influence architecture, engineering standards, automation and governance within a co-managed delivery model. You will work across structured … including: 34 days annual leave (including public holidays) Access to earned pay before payday Company pension scheme Generous occupational maternity/paternity pay Ongoing learning and development opportunities Health Cash Plan after probation (covering dental, optical, therapies, maternity/paternity, prescriptions and more) Opportunities for career progression ...

quickly together, embracing collaboration and change as part of start‐up life. Individuals thrive here if they enjoy taking ownership, wearing multiple hats and learning quickly, and are comfortable going beyond core hours when work demands it – not because it is expected every day, but because seeing progress matters. … Integrate performance testing techniques across multiple types of simulation (e.g. Gazebo, rosbag‐based workflows). Collaborate with hardware engineers, systems architects and AI/ML specialists to integrate embedded software and test frameworks into the overall system. Participate in code reviews, performance optimisation and comprehensive testing (unit, integration and system ...

quickly together, embracing collaboration and change as part of start-up life.? Individuals thrive here if they enjoy taking ownership, wearing multiple hats and learning quickly, and are comfortable going beyond core hours when work demands it - not because it is expected every day, but because seeing progress matters. … Integrate performance testing techniques across multiple types of simulation (e.g. Gazebo, rosbag-based workflows).? Collaborate with hardware engineers, systems architects and AI/ML specialists to integrate embedded software and test frameworks into the overall system.? Participate in code reviews, performance optimisation and comprehensive testing (unit, integration and system ...

quickly together, embracing collaboration and change as part of start-up life.? Individuals thrive here if they enjoy taking ownership, wearing multiple hats and learning quickly, and are comfortable going beyond core hours when work demands it - not because it is expected every day, but because seeing progress matters. … Integrate performance testing techniques across multiple types of simulation (e.g. Gazebo, rosbag-based workflows).? Collaborate with hardware engineers, systems architects and AI/ML specialists to integrate embedded software and test frameworks into the overall system.? Participate in code reviews, performance optimisation and comprehensive testing (unit, integration and system ...

based on user feedback Strong problem-solving skills and ability to work independently with minimal supervision Nice-to-have Bonus: Experience with AI/ML systems, LLMs, or working in regulated industries (fintech, compliance, etc.) Bonus: Experience with high-scalable AWS architecture Our tech stack NodeJS/Typescript NextJS Python … actively, embrace feedback and foster a collaborative environment where ideas are shared openly. You are confident in your expertise while recognising the value of learning from others and adapting to change. Budget: Base salary £60k-£90k Equity: 0.5-1.0% Negotiable, depending on preferences The interview process ⏳ We are seeking ...

Knowledge of IAM design, network security controls, encryption, secrets management, and cloud identity principles. Understanding of modern cloud architectures (serverless, microservices, managed AI/ML services) and their associated security risks. Ability to collaborate effectively with AI engineers, developers, and cloud teams to ensure secure implementation of AI workloads. Desirable … vector databases, model APIs, or data pipelines used by LLMs. Knowledge of responsible AI principles, model governance, or AI-specific threat modelling (e.g., adversarial ML, data poisoning, prompt injection). Background working in regulated industries such as Financial Services or Insurance. Strong stakeholder communication skills, including the ability to influence ...

Models (LLMs). Perform prompt engineering and optimise prompts for enterprise-scale use cases. Develop AI-driven applications using Python and modern AI/ML frameworks. Integrate Gen AI capabilities with enterprise systems, APIs, and data platforms. Collaborate with business stakeholders and architects to translate requirements into AI solutions. Ensure … knowledge/experience: Hands-on experience with Generative AI and Large Language Models (LLMs). Strong programming skills in Python. Experience with AI/ML frameworks such as TensorFlow, PyTorch, LangChain, or similar. Experience in prompt engineering and model integration. Exposure to cloud platforms (AWS, Azure, or GCP). ...

Identify performance or reliability bottlenecks and propose improvements. Required Qualifications & Experience Strong experience with Python and Django. Familiarity with Torch (PyTorch) for analytical or ML workloads. Proficiency in SGLang or willingness to learn domain-specific languages. A keen sense of system design and desire to build elegant, maintainable solutions. General … time streaming architectures. Familiarity with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes/Docker). Exposure to data pipelines, analytics workflows, or ML deployment. Experience working in startup or product-led teams. Why Zuma Labs? Work in a high-impact startup environment where your work immediately affects ...

schema validation, completeness, freshness, thresholds, and automated alerting. Enhance end-to-end pipeline resilience, monitoring, observability, failure handling, and recovery mechanisms. Integrate AI/ML features to boost reliability, anomaly detection, and operational efficiency. Collaborate closely with Data Product teams, Analytics Engineering, and Data Science to deliver production-grade data … expectations. Preferred Experience: Exposure to AI-enabled pipeline capabilities, such as anomaly detection or intelligent monitoring. Good understanding of MLOps or supporting deployment of ML models into production environments. Experience with CI/CD automation, testing frameworks, and observability tooling. Contracting Route: Timesheets via Umbrella Company This is an exceptional ...

data enabled future. Key Responsibilities Define and maintain conceptual, logical, and physical data models that accurately reflect business processes and support analytics, AI/ML, and operational needs Translate business requirements into robust data entities, attributes, relationships, and constraints; ensure traceability from requirements to models Establish and enforce GDM modelling … strategies) Drive data integration design across sources (CDC, event streaming, APIs), mapping source to target, resolving conflicts, and handling historical changes Support AI/ML readiness by modelling features, aggregations, and histories; collaborate on feature stores and model input/output schemas Embed privacy and security requirements into models ...

requirements. Drive engineering quality: establish CI/CD pipelines, testing strategies, code review standards, and incident response processes. Collaborate closely with the AI/ML engineer to integrate agentic AI capabilities into the core product experience. Optimise platform performance – reduce API latency, improve app responsiveness, and ensure 99.95%+ uptime. … Exchange Commission, Financial Industry Regulatory Authority, SOC 2). Experience integrating open banking APIs (e.g. GoCardless, Plaid, or similar). Exposure to AI/ML integration in production – working alongside LLM-powered features or agentic systems. Experience building and scaling engineering teams from early stage. Previous startup founding ...

requirements. Drive engineering quality: establish CI/CD pipelines, testing strategies, code review standards, and incident response processes. Collaborate closely with the AI/ML engineer to integrate agentic AI capabilities into the core product experience. Optimise platform performance – reduce API latency, improve app responsiveness, and ensure 99.95%+ uptime. … Exchange Commission, Financial Industry Regulatory Authority, SOC 2). Experience integrating open banking APIs (e.g. GoCardless, Plaid, or similar). Exposure to AI/ML integration in production – working alongside LLM-powered features or agentic systems. Experience building and scaling engineering teams from early stage. Previous startup founding ...

Senior AI/ML Engineer Shaping AI for individuals and business London (Hybrid, 3 days/week) Up to £120k + 10% bonus + £20k equity We're building AI that actually matters. AI is at the centre of every business, what you're working … learning at scale for some of the world's most ambitious organisations and individuals looking to better themselves. As a Senior AI/ML Engineer at Multiverse, you won't just ship models. You'll own the full lifecycle, influence our product roadmap, and leave a tangible mark ...

with LLMs such as OpenAI/ChatGPT, Google Gemini, Nvidia, and Writer . Work Across the Commerce Ecosystem: Support the integration of AI/ML capabilities with enterprise platforms, helping connect data and services across Commerce, PXM, CDP, DAM, CMS, and CRM systems. Develop and Maintain Data Solutions: Design … customer data. Contribute to Delivery & Engineering Excellence: Collaborate within agile delivery teams, contributing to solution design, development best practices, and DevSecOps processes, while learning from senior engineers and architects across the Accenture Data & AI community. ...

Azure Data Lake). Familiarity with Microsoft Purview and broader governance practices. Dynamics 365 CE and FO integration and analytics. Exposure to AI/ML enablement in Microsoft ecosystem (e.g., Azure ML/AI Foundry/Azure OpenAI), particularly where analytics feeds AI-powered apps. Experience designing BI/data ...

Contract (Inside IR35) Duration: 6 Months Job Summary: Our client is seeking a skilled and innovative Generative AI Engineer to join our AI/ML team. In this role, you will design, develop, and deploy cutting-edge generative models-including LLMs, diffusion models, and GANs-to solve real-world problems … ethical and responsible AI development , including bias mitigation and safety evaluations. Essential Skills, Experience, and Abilities: Strong programming skills in Python and experience with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). Solid understanding of deep learning, NLP, and generative modeling techniques . Experience with training and fine ...

Middleware Integration: Practical experience building recipes or connectors in Workato to trigger AI workflows from external business events is a strong plus. · Data & Traditional ML: Experience with Databricks for data engineering (PySpark) or building classical ML models (Scikit-Learn, XGBoost) is beneficial for handling complex data pre-processing and hybrid ...

range of domestic, agricultural, and enterprise sectors. They operate over 75 depots and 800+ tankers. This client are looking to add a talented Data & ML Engineer to join their team as they enjoy a sustained period of growth. What you'll do: Take ownership of the Microsoft Fabric ecosystem (OneLake …/CD practices, cost efficiency, and reliability Oversee enterprise BI platforms (Power BI, Qlik), managing semantic models, performance tuning, and automated refresh processes Support ML/AI initiatives by developing feature pipelines, enabling MLOps, and driving model deployment with Azure AI/ML/OpenAI Establish and maintain data quality ...

with client business goals. Serve as technical design authority for AWS, guiding team architectural standards and decision making. Support the delivery of AI/ML and Gen AI proof of concepts, leveraging cloud-native services. Cloud Strategy, Automation & Governance Develop and refine cloud landing zones, infrastructure-as-code, and automation … frameworks such as 7Rs. Standardise tooling, and governance to improve technical efficiency and consistency across teams. Stay current with and integrate emerging technologies (AI, ML, serverless) to maintain technical edge. People Leadership & Team Development Provide technical mentoring for cloud excellence, focusing on best practices, CI/CD and operational excellence. ...

deployment → monitoring → iteration Make pragmatic trade-offs between speed, quality and technical elegance Product & User Impact Translate messy real-world user problems into testable ML solutions Partner closely with Product to ensure models improve user trust, confidence and discovery Focus on feature value, ROI and the signals that truly matter … frameworks and evaluation pipelines Decide where data investment matters most Technical Direction & MLOps Establish pragmatic MLOps practices (deployment, monitoring, iteration) Build scalable but lightweight ML pipelines in AWS alongside engineering Ensure models are robust, reliable and safe for production Team & Culture Set the technical bar for data science Mentor future ...