101 to 125 of 156 Machine Learning Jobs in the City of London

solutions to customer needs. Desirable Experience selling into government or regulated sectors. Familiarity with CRM tools (e.g. Sugar, HubSpot). Understanding of AI/ML applications in enterprise environments. This is a great opportunity to join a mission-driven, rapidly growing tech company where your work makes a real impact ...

evaluate sensors, build calibration tools, implement 3D pipelines, and ensure system robustness for deployment in industrial environments. Your work will directly influence downstream planning, learning, and control systems. What you’ll do: Evaluate and integrate various sensors, experimenting with hardware setups and assessing their data quality based on mounting … geometries to CAD models using techniques like feature extraction, RANSAC, ICP, and outlier handling. Ensure perception data feeds accurately into digital twin simulations and machine learning pipelines. Build robust logging, replay, health checks, and failure detection systems for reliable deployment. Must-have skills: At least 3 years ...

company— want to hear from you. Our client’s mission is to help subscription businesses drive customer growth and predict revenue more accurately using machine learning and AI. Their platform empowers businesses to improve customer loyalty and unlock greater revenue from existing customers. Recently listed in Sifted … health insurance - quality care when you need it most Monthly wellness allowance - use it on gym memberships, yoga, mental health, healthy food & more Annual learning & development budget - invest in your growth ·Hybrid working - 3 days in the office, 2 days where it suits you Top-tier equipment - everything ...

currently the youngest AI business to raise a Series B from the YCombinator portfolio! They have built a product that leans into blending machine learning models and data annotation to help businesses save time and money! What You’ll Get This is a key hire ...

Outside IR/35 Were looking for a Data Engineer with strong MLOps ownershipsomeone who builds reliable data pipelines and designs, runs, and improves ML pipelines in production. You wont be training models day-to-day like a Data Scientist; instead, youll enable Data Science by delivering high-quality datasets ...

team Work closely with customers to turn real operational workflows into production systems Who you are Senior engineering leader with strong AI/ML and complex systems experience Comfortable building from first principles in ambiguous environments Hands-on, pragmatic, and delivery-focused Builder mindset with high standards ...

added advantage IT Services & Transformation Selling (must‐have) The candidate must be able to sell: Digital engineering Cloud migration/modernization AI/ML use cases (personalization, pricing, forecasting, chatbot/guest journey automation) Testing, integration, platform engineering Managed services & long‐term transformation programs Ability to manage 6–18‐month ...

Our client is a pioneering technology company delivering laser communications and temporospatial software-defined networking platforms to the aerospace and space industry. Leveraging technology originally developed at a major global tech firm, they are leading ...

Data & AI evangelist - educating stakeholders on possibilities and translating technical outcomes to business value. Data specialist - shaping data science strategy, building production-ready ML models, and embedding best practice. Fixer/problem-solver - helping teams refine requirements, diagnose issues, and drive real commercial outcomes. Day-to-day you will: Translate … complex business problems into research questions with quantifiable objectives. Identify, acquire, and work with structured and unstructured datasets. Build, validate, deploy, and monitor production ML models. Partner with data engineers, ML engineers, architects, and business teams to shape ML initiatives. Present insights clearly through strong data visualisation and storytelling. Uphold ...

world value. What You’ll Bring 3+ years experience in a commercially driven customer environment Strong Python skills and solid grounding in AI/ML fundamentals. Experience with some of Databricks, LangChain , vector databases , or LLM orchestration tools . Knowledge of RAG pipelines , transformers , and modern AI architectures . Understanding … plus). Recent, hands-on experience with applied LLM projects . Strong communication and stakeholder engagement skills. A Master’s degree in Computer Science, ML, or AI is preferred but not required. The Opportunity Be part of an ambitious AI journey - already 70% built, with big plans for the next ...

sector. The role focuses on driving new business acquisition, expanding strategic accounts, and positioning technology solutions including Digital Transformation, Cloud, Data & Analytics, AI/ML, and Application Services. The ideal candidate will have a strong network within BFSI enterprises and a proven track record in consultative enterprise sales. Key Responsibilities … deals and long sales cycles. Solution Selling & Market Positioning Position technology services such as Cloud Migration, Digital Engineering, Core Modernization, Data Platforms, AI/ML, and Cybersecurity. Collaborate with pre-sales, delivery, and practice teams to create tailored BFSI solutions. Understand regulatory requirements and technology trends impacting BFSI clients. Leadership ...

advanced AI systems that deliver real business impact. Responsibilities as a Principal AI Engineer: Lead end‐to‐end delivery of scalable, resilient AI/ML pipelines aligned to business goals. Build and deploy advanced ML, DL, and LLM solutions, including RAG, agentic architectures, and evaluation frameworks. Mentor engineers in ML ...

Siena Partnership are working with a leading financial services organisation is seeking a Senior Full Stack AI/ML Engineer for an initial 6-month contract (with the potential to extend or go perm) . This role focuses on taking AI models built by a third-party provider and turning … them into robust, production-grade systems , while helping establish a long-term internal AI/ML engineering capability. What you’ll do Deploy and operationalise AI/ML models into live production environments Build observability, monitoring, and continuous evaluation to manage model performance and drift Design and implement CI/ ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...

Outside IR/35 Were looking for a Data Engineer with strong MLOps ownershipsomeone who builds reliable data pipelines and designs, runs, and improves ML pipelines in production. You wont be training models day-to-day like a Data Scientist; instead, youll enable Data Science by delivering high-quality datasets … reproducible training pipelines, robust deployments, and monitoring that keeps ML systems healthy and trustworthy. What youll do Design, build, and operate scalable data pipelines for ingestion, transformation, and distribution Develop and maintain ML pipelines end-to-end: data preparation, feature generation, training orchestration, packaging, deployment, and retraining Partner closely with ...

will have hands-on experience with frameworks such as LangGraph and a strong understanding of the practical implementation and deployment of agentic AI/ML solutions. Key Responsibilities: • Design, build, and deploy agentic AI systems, leveraging modern frameworks. • Develop and maintain scalable AI workflows using LangGraph and related tools. • Collaborate … integrate AI agents into real-world applications. • Write clean, efficient, and testable Python code. • (Optional) Apply data science techniques to train and fine-tune ML or deep learning models. Required Skills: • Strong proficiency in Python and related libraries. • Experience with agentic AI architectures and autonomous AI agents. • Hands ...

engineers to deploy features end-to-end What they’re looking for New Grad/Early Career, ideally MSc or PhD in CS/ML/NLP (or related) Strong applied ML research background, ideally with publications in top venues such as: NeurIPS, ICML, ICLR, ACL, EMNLP, AAAI (added bonus ...

cross-functional teams to define requirements and deliver innovative tools. Ensure reliability, scalability, and performance of distributed systems handling massive datasets. Deploy and monitor ML models in production environments using Vertex AI, Docker, and Kubernetes. Required Skills & Experience Strong proficiency in Python for AI/ML workflows . Strong proficiency … . Expert-level SQL and experience with BigQuery and vector databases (Pinecone, Weaviate, Vertex AI Search). Proven track record in MLOps and deploying ML models at scale. Experience moving LLM-based prototypes into production environments with thousands of users. Background in building internal tooling, CRM enhancements, or sales-tech ...

Essential skills: 15+ years overall in software/solution architecture with 7 + years in cloud (Azure) and 5 + years in AI/ML or Azure AI solutioning. Proven experience leading production-grade solutions using Azure OpenAI , Azure AI Foundry , Azure AI Document Intelligence, Azure Data Factory, Azure ML ...

organization operating at scale in AI-driven and data-intensive environments. You’ll work on building high-performance data pipelines, supporting advanced analytics and ML-driven initiatives, and ensuring robust, scalable data infrastructure across multiple domains. What You’ll Do Design, build and maintain scalable data pipelines for large, complex … Process and integrate structured and unstructured data from multiple sources Ensure data quality, reliability, and performance end-to-end Collaborate closely with AI/ML teams to deliver production-ready datasets Support data governance, lineage, and documentation in a pragmatic, impact-focused way What You Bring Senior level Data Engineering ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...

Engineering & Solution Delivery Develop, design, and implement scalable, maintainable, secure, and observable AI solutions-automating decision-making, integrating with enterprise platforms, embedding LLMs, reinforcement learning, and APIs, and delivering measurable business outcomes. AI Lifecycle Ownership & Responsible AI Implement all components of the AI lifecycle, including data preparation, agent building … innovation at speed and scale. Experience in refactoring, optimisation, and writing clean, performant code. Hands-on experience with enterprise and cloud environments, ideally Azure ML, GCP Vertex AI, or Azure Foundry. Familiarity with AI architectures, LLMs, vector databases, and agent frameworks (e.g., Google ADK, LangChain/LangGraph) is a significant ...