201 to 225 of 605 Machine Learning Jobs in London

oral and written communication skills. PREFERRED QUALIFICATIONS BSc/MSc in relevant field (Computer Science, Engineering or related field). Experience with AI and machine learning technologies. Experience with DevOps, SRE, infrastructure as code, Terraform, AWS. General knowledge of Linux, Docker, Kubernetes. Experience with all stages ...

MaaS offerings, including Qwen (Tongyi) model family, PAI platform, and GPU computing services - Develop and execute go-to-market strategies for AI/ML products tailored to the European market - Build a robust sales pipeline through proactive prospecting, industry events, ecosystem partnerships, and referral networks - Collaborate with solution architects … meetups, and industry forums across Europe Qualifications: Qualifications Required: - 3+ years of experience in business development, sales, or partnerships within cloud computing, AI/ML, or enterprise software industries - Demonstrated track record of achieving and exceeding sales targets - Strong understanding of AI/ML technologies, including large language models, generative ...

Bring Overall 9+ years of experience in engineering, machine learning & LLMs. 6+ years of hands‐on experience in building & deploying AI/ML/Gen AI solutions in large business critical applications. 2+ years of experience in developing Gen AI products using variety of LLMs & frameworks. 1+ years … curious technically to evaluate & test new technologies in Gen AI space. Proven ability to work with large structured & unstructured datasets and deploy AI/ML/Gen AI solutions through automated pipelines. Experience with leveraging, training and fine‐tuning Foundation Models including multimodal inputs and outputs. Strong experience working with ...

tooling Solid Python knowledge Familiarity with Claude and similar frontier models Production experience using LangChain PhD, MSc or BSc in a AI/ML or similar discipline Desirable RAG architectures, embeddings, and vector databases Prompt management, evaluation, and observability Cloud deployment (AWS, Azure, or GCP) Enterprise concerns: security, governance ...

such as AWS, Azure, or GCP. Familiarity with containerisation and orchestration technologies (e.g. Docker, Kubernetes). Exposure to MLOps practices or deploying AI/ML models into production environments. Experience working in agile or fast-paced delivery teams . ...

inference and data processing Own cloud infrastructure (AWS), deployment pipelines, monitoring, and security controls Collaborate with the AI research team to deploy and serve machine learning models in production Establish engineering best practices across code review, testing, CI/CD, and documentation Data Architecture & Integration Design and maintain … requirements Comfortable making architectural decisions that balance speed, quality, and regulatory compliance Also Valuable Experience with healthcare data interoperability (FHIR, HL7, DICOM) Exposure to ML model serving, MLOps pipelines, or ML frameworks (TensorFlow, PyTorch) Understanding of GDPR, HIPAA, or UK Data Protection Act compliance Experience with Infrastructure as Code (Terraform ...

greenfield product at an early stage Own a core product pillar (audio + AI) from day one Collaborate across embedded, cloud, and ML teams High autonomy in a low-ego, high-performance environment Competitive salary + equity Strong long-term growth and learning opportunities The Role You’ll take … full ownership of the audio subsystem, spanning real-time embedded processing through to cloud-based audio pipelines and ML integration. This role sits between embedded engineering and backend/AI — ideal for someone who enjoys both low-level systems and higher-level software. Key Responsibilities Design and build ...

delivery of complex AI projects across global teams Mentor engineers and data scientists and drive best practice Key requirements Strong background in AI, machine learning or data science Deep experience with LLMs and modern GenAI frameworks Experience designing AI architectures such as RAG and agent-based systems Strong ...

love using data to tell a story. We’re also the world’s largest team of data scientists, data engineers, and experts in machine learning and AI. Our focus is on big problems using the latest tech, serious brain power, and deep knowledge of just about every industry. ...

Stats: You must have an excellent grasp of Linear and Logistic Regression . You understand the assumptions, limitations, and interpretability of these models. Advanced ML: Experience with boosting models is essential for our higher-complexity tasks. Analytics Patterns: A core ability to creatively analyse a raw dataset and spot trends ...

with colleagues across business units to translate needs into practical AI-enabled solutions. Required Skills & Qualifications: Proven experience developing, tuning, and deploying AI/ML models using frameworks. Experience with Azure AI Foundry Hands-on experience with agentic AI tools and orchestration frameworks. Proficiency in Python and familiarity with … Awareness of data governance, secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated industries is advantageous. In the first instance ...

with colleagues across business units to translate needs into practical AI-enabled solutions. Required Skills & Qualifications: Proven experience developing, tuning, and deploying AI/ML models using frameworks. Experience with Azure AI Foundry Hands-on experience with agentic AI tools and orchestration frameworks. Proficiency in Python and familiarity with … Awareness of data governance, secure handling of sensitive data, and regulatory considerations. Knowledge of MLOps/DevOps practices, including CI/CD pipelines for ML models. Understanding of reinforcement learning, multi-agent systems, or advanced optimization methods. Previous experience working in regulated industries is advantageous. xehkeey In the first ...

place to scale safely Collaborate with the Machine learning team to maximise value from our internal and external data through cutting‐edge ML models Be a member of the Borrowing Credit Leadership team which drives our vision to build a best in class credit function What … offer flexible working hours and trust you to work enough hours to do your job well, at times that suit you and your team. Learning budget of £1,000 a year for books, training courses and conferences And much more, see our full list of benefits here Our interview ...

Architect, DevOps Engineer, or equivalent) Ability to translate business requirements into scalable, secure cloud architectures Strong grasp of data platforms, analytics, and AI/ML-driven solution design Proficiency across modern cloud patterns; serverless, containerised, microservices, CI/CD Deep knowledge of security architecture: identity, access management, encryption, compliance Experience … event-driven architecture, and hybrid connectivity Degree in Computer Science, Software Engineering, or a related field Bonus points for: AWS Specialty certifications (Advanced Networking, Machine Learning, Security) Multi-cloud experience with Azure or Google Cloud Important: All offers are subject to BPSS and SC security clearance, which requires ...

Fraud Operations Director in Fintech, you will work in a highly collaborative environment with extensive amounts of data to research and develop deep learning models to solve real-world problems and apply them to tasks such as identifying bad actors, preventing fraud, building anomaly detection models, and analytics … perform shared goals. Successful outcomes in this role will significantly impact the business. Responsibilities: Lead the development and optimization of fraud detection systems using machine learning and rule-based engines. Work closely with management, product, engineering, compliance, legal, and security teams to align, present, and implement ...

Head of AI Type: Permanent The Opportunity A global professional services organisation is seeking an AI Capability Leader to design and scale its AI learning and community strategy. This senior role focuses on building practical, market-aligned AI capability while supporting enterprise clients and internal go-to-market activity. … Role You will lead the design and evolution of AI learning pathways aligned to current and emerging market needs, working across areas such as GenAI, machine learning, data science, and AI engineering. Partnering closely with commercial and delivery teams, you'll ensure learning programmes ...

WILL BRING TO THE TEAM MUST HAVE SKILLS Strong Python engineering skills, writing clean, modular, and production-ready code. Data science experience, applying machine learning and statistical models for Marketing Mix Modelling (MMM) and Econometrics. Excellent communication skills, able to explain complex concepts to both technical ...

Knowledge of APIs, system integration, and microservices Client-facing experience or delivery-focused roles Strong problem-solving and communication skills Desirable: Exposure to AI, ML, or data platforms DevOps, CI/CD, or infrastructure as code experience Consulting or technical delivery background Location: UK Hybrid, with occasional client visits ...

major features, platforms, and technical initiatives Collaborate with technical leads and DevOps on system scalability, performance, and reliability Ensure data platforms are AI/ML-ready, with scalable infrastructure and clean, well-structured data pipelines Collaborate with data science and analytics teams to enable model deployment, automation, and MLOps best ...

Drive integration of structured (e.g., financial data, CRM) and unstructured (e.g., filings, call transcripts, news) data to enable advanced insights. Oversee data engineering and ML feature pipelines in collaboration with data teams.* **Productization & Delivery** - Convert proofs-of-concept into scalable, enterprise-grade tools. Embed AI solutions into banker workflows … Collaborate with risk, legal, and compliance teams on AI model governance.* **Team Building & Leadership -** Build and lead a high-performing team of AI engineers, ML specialists, and applied data scientists. Foster a culture of innovation, delivery excellence, and business alignment.**Qualifications Must-Have Skills & Experience*** Significant proven data science/ ...

reimagining value creation capabilities. They are utilising cutting-edge AI to generate performance insights on each aspect of the investment lifecycle. Responsibilities: Build machine learning predictive models to anticipate/avoid asset downtime and reducing customer churn Evaluate … optimise all models, identifying areas for development Work end-to-end both building and deploying models Stay updated with the latest developments in ML/AI, and related fields to keep the company at the forefront of technological advancements Stay updated on emerging technologies, trends, to recommend and implement innovative ...

Drive integration of structured (e.g., financial data, CRM) and unstructured (e.g., filings, call transcripts, news) data to enable advanced insights. Oversee data engineering and ML feature pipelines in collaboration with data teams. Productization & Delivery – Convert proofs‐of‐concept into scalable, enterprise‐grade tools. Embed AI solutions into banker workflows … Collaborate with risk, legal, and compliance teams on AI model governance. Team Building & Leadership – Build and lead a high‐performing team of AI engineers, ML specialists, and applied data scientists. Foster a culture of innovation, delivery excellence, and business alignment. Qualifications – Must‐Have Skills & Experience Significant proven data science/ ...

bridge between engineering, product, and commercial. What I’m Looking For 8+ years of engineering leadership within B2B SaaS, ideally in AI/ML or data-focused environments. Experience growing teams through start-up to scale-up (Series A/B); time in both early-stage and mature environments … continuous delivery, and high-performing lean teams. People-first leadership style, with a proven ability to build and nurture high-performing teams. Exposure to machine learning, NLP, or financial data products is highly advantageous. Comfortable working in fast-moving, ambiguous environments where both execution and strategic vision matter. ...

Role - Research ML Engineer 📌 Location - London, 2 days per week 💸 Salary - up to £200K plus equity 🏢 Domain - Developer Tooling I'm working with a start-up who are building fully autonomous coding agents, their product can understand systems context and, with minimal human input, write code. They … with experience from companies like; Google DeepMind, Spotify, Sourcegraph & Meta. What We Are Looking For 5+ years of industry or academic experience as a Machine Learning Engineer, Applied Scientist, or Research Scientist. Search & Retrieval: Deep experience designing and scaling state-of-the-art systems (e.g., multi-stage retrieval ...

between cost, latency, and production-scale performance. What you'll bring Proven extensive lead-level engineering experience delivering sports insights or sports data–driven ML systems, with clear ownership of technical direction, mentoring, and delivery. Deep understanding of sports data, including hands-on experience working with event data, tracking data … other high-volume sports datasets, and converting these into actionable analytical or predictive insights. Working knowledge of modern ML techniques, including Generative AI, and how emergent models can extract insights from multi-modal sports data (e.g., numerical, spatial, video, or metadata). Advanced Python expertise with strong hands ...