601 to 625 of 737 Machine Learning Jobs in London

Job Description: Redis cluster setup Kafka/Flink streaming pipelines S3 Data pipeline Real time micro batches implementation (5 minutes, hourly, daily) Mongo/Atlas as alternative implementation (we might land with S3 instead) SageMakerMLOps ...

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 ...

London/Hybrid Working style Remote-first with periodic in-person working sessions Reports to CTO (fractional; Gregory Wheeler, Martingale GmbH) Works with Principal ML Engineer (Zifan); CTO; Founders Start date March 2026 Probation 3 months Role type Full-time, permanent Salary & Benefits £70-95k, Bonus, Equity, Other benefits … reconciliation. • Build and operate async processing infrastructure: queues, workers, schedulers, with attention to reliability patterns (dead-letter queues, safe reprocessing, backpressure). AI/ML Operations Support • Partner with the ML engineer on production deployment of AI/ML models and agentic workflows: containerisation, versioning, controlled rollouts, and regression testing. ...

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 ...

high-impact solutions. Mentor and lead cross-functional AI teams, building reusable assets and delivery excellence. Background & Experience PhD or equivalent in Computer Science, ML, AI, or a related field (or outstanding equivalent experience). Extensive experience designing and deploying enterprise AI/ML solutions in production. Proven leadership … e.g. financial services, healthcare). Track record of thought leadership (publications, patents, open source, or industry impact). Technical Excellence Expert Python and modern ML frameworks (PyTorch, TensorFlow). Strong experience with Generative AI tooling (e.g. LangChain, LangGraph or similar). Deep understanding of LLMs, prompt engineering, RAG, vector databases ...

embedding optimization Chunking and document preprocessing strategies Evaluation and regression testing harnesses Develop APIs, microservices, and serverless GenAI workflows for scalable, secure deployment. ML/LLM Engineering & LLMOps Work across AI/ML platforms such as Azure ML, AWS SageMaker, Vertex AI, Databricks, Modal, and Fly.io. Deploy and manage vector … with PromptOps, LLM observability, and evaluation tooling. Understanding of Responsible AI, safety, bias mitigation, governance, and compliance frameworks. Background in Computer Science, AI/ML, Engineering, or a related technical discipline. Experience deploying, fine-tuning, or serving open-source LLMs in production. Staffworx is a UK-based Talent & Recruiting Partner ...

tools (e.g., Tableau, Power BI, Looker, Qlik) and how to connect, model, and optimize for self-service analytics. · Familiarity with data science and ML workflows (feature engineering, experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g. ...

tools (e.g., Tableau, Power BI, Looker, Qlik) and how to connect, model, and optimize for self-service analytics.· Familiarity with data science and ML workflows (feature engineering, experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g. ...

tools (e.g., Tableau, Power BI, Looker, Qlik) and how to connect, model, and optimize for self-service analytics.· Familiarity with data science and ML workflows (feature engineering, experimentation, model training/deployment, RAG pipeline development, prompt engineering) and tools/languages such as Python, Spark, notebooks, and ML frameworks (e.g. ...

scalable and well-architected system design Excellent communication skills, including working with stakeholders at all levels Desirable Knowledge of emerging technologies (e.g., AI/ML tools) Previous senior/lead engineering experience Experience running large multidisciplinary projects Line management experience Experience interviewing and supporting technical hiring Experience contributing to bids … design and data to help public sector organisations deliver outcomes that genuinely improve lives. You'll join a thoughtful, collaborative community that values diversity, learning and openness. Benefits include: 30 days holiday + bank holidays 2 paid volunteer days Enhanced maternity/paternity leave 5% employer pension contribution Health ...

They have deep understanding of digital transformation of complex legacy IT environments to new native digital environments – focussing on Data Modernisation and AI/ML to solve enterprise IT challenges. The knowledge of IoT, DevOps, Application Modernization to solve complex process industry challenges will be an advantage. Understanding … with hands-on expertise in services such as EC2, S3, RDS, Redshift, Glue, Lambda, Athena and Kinesis. Desirable: AI/Gen AI/ML services (e.g., SageMaker, Bedrock, Lex, Comprehend, Transcribe). Desirable: Experience with architecting and implementing data pipelines, data lakes, and data warehousing solutions optimised for GenAI workloads. ...

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 ...

using tools such as Azure Data Factory, Databricks, PySpark, SQL, and Python . Develop scalable ELT/ETL pipelines to support analytics, AI/ML, BI, and operational systems. Implement data quality monitoring, lineage, validation, and governance to ensure trusted data products. Build and optimise data models for analytical … define KPIs and data products that drive measurable value. Support feature engineering, model data pipelines, and AI use cases (e.g., demand forecasting, optimisation, clustering, ML pipelines). Enable business intelligence platforms (e.g., Power BI, Tableau ) with trusted, well-modelled datasets. Leadership & Stakeholder Management Lead, coach, and mentor data engineers (including ...

Position: ML & AI Engineer Location: London, UK (Hybrid-3 days a week from office) long term contract position Program Scope: Developing and provisioning of infrastructure that support agentic workflows across both Azure and GCP Data science expertise to help shape the agentic solution design of Coach AI as well … single experience point Evaluation methods - continued automation of both deterministic and generative conversations in a scaled and simulated way Key Skills/Knowledge: ML & AI Engineer Must haves Python literacy - min 2years+ working on production grade LLM based applications Software Engineering - strong understanding of microservices architecture, CI/CD pipelines ...

Databricks. In this role, you will define both high-level and low-level designs, shape scalable and secure data and AI/ML platform capabilities, and drive seamless integration with core enterprise systems. The ideal candidate combines deep cloud architecture expertise, strong data engineering and AI/ML platform experience … other data/AI services within the ecosystem.The ideal candidate brings a strong blend of cloud architecture, data engineering, and AI/ML platform experience, along with the ability to translate business requirements into scalable and secure technical solutions. Key Responsibilities: Architecture & Design Define ...

/GCP/Azure) Experienced building real pipelines — not just notebooks Curious about how financial systems actually work Bonus points for: Exposure to ML workflows Familiarity with dbt, Airflow, Docker Experience handling financial or semi-structured data Interest in LLM infrastructure and vector databases Finance background is not required. Intellectual … defined, low-risk task lists You want heavy supervision You are uncomfortable working directly with senior stakeholders You are looking for a purely academic ML role Upside Direct learning from investors Rapid technical growth Path toward AI Engineer/ML Engineer/Quant Data roles High visibility within ...

full-stack development and AI system design to complex enterprise environments. This role demands hands-on experience in building and deploying AI/ML solutions, a strong grasp of software engineering principles, and proficiency with cloud platforms. You will play a key role in developing scalable, intelligent systems that drive … pipelines. AI System Development: Implement and optimize AI models, ensuring they are scalable, maintainable, and production-ready. Work on GenAI, Agentic AI, and classic ML solutions. Enterprise Integration: Integrate AI solutions with existing enterprise systems and ensure seamless operation within the client and #39;s technology stack. Collaboration: Work closely ...

full-stack development and AI system design to complex enterprise environments. This role demands hands-on experience in building and deploying AI/ML solutions, a strong grasp of software engineering principles, and proficiency with cloud platforms. You will play a key role in developing scalable, intelligent systems that drive … pipelines. AI System Development: Implement and optimize AI models, ensuring they are scalable, maintainable, and production-ready. Work on GenAI, Agentic AI, and classic ML solutions. Enterprise Integration: Integrate AI solutions with existing enterprise systems and ensure seamless operation within the client's technology stack. Collaboration: Work closely with cross ...

volume, low-latency payments data use cases across clearing, settlement, liquidity and regulatory reporting. The position focuses on cloud-native data platforms, AI/ML enablement and governance-aligned delivery in a highly regulated, large-scale banking environment. Key responsibilities: 1) Data Platform Strategy & Architecture Define and own a multi … cases. Support data quality, reconciliation and lineage requirements critical to payments operations and downstream risk, finance and regulatory reporting. 3) Emerging Technology & AI/ML Enablement Assess and selectively adopt emerging data and analytics technologies (e.g., distributed query engines, open table formats, streaming frameworks, graph and NoSQL stores). Evaluate ...

pipelines at scale Background in operations research or supply chain optimisation Exposure to LLMs as signal sources — extracting structured market intelligence from unstructured text ML Skills We're Looking For This role sits at the intersection of classical econometrics and modern machine learning. You don't need … outperform neural approaches on structured data, and vice versa. Strong intuition for regularisation, hyperparameter tuning, and avoiding leakage in time series cross-validation. Deep Learning for Sequences. Hands-on experience with temporal architectures - LSTMs, GRUs, Temporal Fusion Transformers, N-BEATS, or similar. Understanding of attention mechanisms and when transformer ...

shipped product Tech Stack You don't need experience with everything listed, but this is what you'll be working with: Python: backend and ML Ops JavaScript/React: frontend AWS: product infrastructure Azure: AI tooling and related services LLM/ML: experience working with and managing LLMs Work Setup ...

Computer Science, Data Engineering, or related field. Certifications in cloud platforms (e.g., Azure Data Engineer, GCP Associate Cloud Engineer). Familiarity with AI/ML applications in customer engagement and personalisation. Why Join Accenture? Work with cutting-edge technologies and global clients. Be part of a diverse, inclusive, and innovation … driven culture. Access world-class learning resources and career development programmes. Join a team that values stewardship, integrity, and client value creation. What’s in it for you: Our Total Rewards consist of a competitive basic salary, annual performance bonus, opportunities to acquire equity and a wide range ...

Architecture. Experience in AI-enabled customer experience transformation. Degree in Computer Science, AI, or related field (or equivalent practical experience). Cloud, AI/ML, or CX vendor certifications (AWS/Azure/GCP, Genesys Cloud, OpenAI, Hugging Face, etc.) are a plus. Flexible/remote working options Private healthcare … life insurance Pension plan Cycle-to-work scheme 28 days paid annual leave (including company-wide wellbeing days) Access to LinkedIn Learning and ongoing development programs If you’re ready to shape the future of AI-driven customer experience and thrive in a collaborative, fast-paced environment ...

with one or more languages (e.g. Python, Java, Scala, Go ) Pragmatic approach to solving problems Nice to have: keen interest in modern AI/ML techniques Why Indicium AI Fast-growing start-up organisation with huge opportunity for career growth Highly competitive salary package along with company bonus A hugely … meaning security and support for new initiatives and global market expansion Pick your own Gear! Macbooks, PCs, Accessories! Drive your development with a personal learning budget ...

plus) Experience building with cloud platforms such as AWS, Azure, or GCP Experience working with AI tools or platforms (LLMs, predictive models, ML infrastructure) Strong understanding of distributed systems patterns and trade‐offs Knowledge of non‐functional requirements—scalability, reliability, performance, observability Bonus points for: Interest in functional programming Experience … plus the ability to work from almost anywhere for up to 90 days per year £500 remote working budget to upgrade your home office Learning & Development $1,000 annual L&D budget for personal and professional growth Vacation & Leave 25 days of annual leave + bank holidays An extra ...