551 to 575 of 1,249 Permanent Machine Learning Jobs

that transform data from operational systems into trusted, analytics-ready assets. Your work will enable high-quality reporting, insight generation, and future AI/ML initiatives across the business. What You'll Do * Build & Maintain Pipelines: Develop ELT/ETL pipelines using dbt, Python, and orchestration tools. * Work with Snowflake ...

team in a fast-paced environment. Preferred qualifications, capabilities, and skills Experience with OMS platforms Knowledge of KDB Familiarity with AI/ML concepts Experience with AWS #J-18808-Ljbffr ...

Azure Data Factory. • Drive DevOps best practices including CI/CD, automated testing and infrastructure as code. • Collaborate closely with data engineers, ML engineers and wider technical teams to deliver robust platform capabilities. • Take ownership of key data platform projects and influence engineering direction. • Provide technical leadership and ensure standards ...

Responsibilities: Build and maintain relationships with senior stakeholders across Investment Banks and Hedge Funds Network and headhunt high-calibre Data & AI professionals (Data Scientists, ML Engineers, AI Specialists) Drive new business through strategic development Consult, negotiate, and manage both clients and candidates Manage the end-to-end recruitment process ...

Azure Data Factory. • Drive DevOps best practices including CI/CD, automated testing and infrastructure as code. • Collaborate closely with data engineers, ML engineers and wider technical teams to deliver robust platform capabilities. • Take ownership of key data platform projects and influence engineering direction. • Provide technical leadership and ensure standards ...

data modelling, cleansing and dataset preparation. Experience supporting or developing Power BI dashboards and data visualisations. Familiarity with APIs, automation tools and AI/ML-driven platforms. Strong JavaScript and jQuery skills, including asynchronous handling and AJAX. Knowledge of version control tools such as Azure DevOps. Understanding of UX principles ...

/CD, automation, and platform reliability Running production workloads with high availability requirements Plus, experience with one or more of the following: MLOps or ML platform engineering RAG architectures, embeddings, or vector search Model serving, observability or performance optimisation Data/AI workflow orchestration in Databricks or similar ecosystems ...

based systems. Awareness of secure coding practices and modern cybersecurity threats. Knowledge of principles used in Agile environments. Desirable exposure Any exposure of AI, ML, Cloud or Virtualisation would be considered a plus. Clearance required Due to the nature of the clients' work, you will either already hold ...

range of industries (including Financial Services, Public Sector, and Pharma), delivering programmes that span: Data platform transformation (data lakes, warehouses, pipelines) AI/ML use cases and intelligent automation SaaS implementations and system integrations Cloud-native architectures (Azure, AWS, GCP) This is a hands-on leadership role , ideal for someone ...

Must have experience building data engineering pipelines in Azure Experience in Azure including Azure Fabric, Data Factory and Azure integrated services such as ML Studio, Foundry, Synapse, Cosmos Deep expertise in deploying and scaling generative AI solutions within Azure, including proficiency with databases, Prompt Flow, virtual machines, and Azure Foundry. ...

cataloguing. Exposure to solution architecture principles, particularly within governed environments requiring design authority and formal approval processes. Experience or awareness of AI/ML or AI-assisted analytics implementations within enterprise environments. Desirable Skills Experience supporting or implementing AI-enabled tools such as Copilot for Power BI or similar technologies. ...

platform for enterprise customers (SSO, auditability, compliance ready patterns) Collaborate closely with founders & product · Shape system architecture and API design alongside full-stack and ML engineers · Translate ambiguous product ideas into robust backend implementations · Iterate quickly based on real customer usage and feedback What We’re Looking For Essential ...

Support strategic account leads in identifying opportunities for deepened client engagement. Business-Technical Communication Serve as the trusted bridge between engineering teams (AI/ML, data, DevOps) and non-technical stakeholders. Frame technical progress and limitations in accessible, value-oriented language. Support tech leads by surfacing risks and clarifying feasibility ...

evolve, and making sure we're building towards what matters next. What we're looking for Extensive experience in software or AI/ML engineering, with a substantial portion spent in architecture roles, ideally spanning both platform and solution architecture. Deep, hands-on knowledge of LLM and agentic system design. ...

stakeholders, helping them navigate design choices and achieve measurable business outcomes. Build strategic roadmaps for Data & AI capabilities, supporting predictive analytics, BI, AI/ML and GenAI. Lead workshops to capture requirements, validate design decisions and align business/technology stakeholders. Manage teams across consulting disciplines , fostering an inclusive ...

reconciliation), and how data moves through systems. Experienced in building medium to long term technology roadmaps and strategy. Experience integrating and operating AI/ML, or agent‐enabled components as part of broader systems, with attention to reliability, explainability, operational controls, and failure modes. Experience designing systems where data quality ...

design). Design scalable, secure data solutions leveraging cloud platforms (Azure, AWS, or Oracle). Ensure data architecture supports advanced analytics, BI, AI/ML, and operational reporting. Oversee data architecture aspects of major change initiatives and programmes. Produce high-quality architecture deliverables and ensure they are integrated into delivery ...

similar Stakeholder managemenT Useful but not essential: Lakehouse or cloud-native data platform architecture experience Data lakes, object storage, and large-scale analytical processing ML or advanced analytics exposure AWS security, networking and access control GDPR and data governance awareness DAY TO DAY No two days will look the same ...

innovative suite of technology, including: · Advanced forecasting and planning tools · An Audience/ID Graph optimised for Addressable TV audience building · AI/ML algorithms for campaign optimisation · Cross-platform measurement capabilities At Broadlab, creativity and technology come together in a “one stop shop” solution that ensures campaigns are planned ...

with the ability to challenge convention. Strong understanding of automation, workflow optimisation, and process re-engineering. Ability to translate complex ideas (including AI/ML concepts) into simple, clear language. Experience working in agile product development environments. Desirable Experience working in regulated environments or with legal workflows. Thorough understanding ...

evolve, and making sure we're building towards what matters next. What we're looking for 12+ years in software or AI/ML engineering, with a substantial portion spent in architecture roles — ideally spanning both platform and solution architecture. Deep, hands-on knowledge of LLM and agentic system design ...

operationally. What you’ll bring. Proven executive leadership building partner engineering teams within enterprise software ecosystems Deep technical fluency in data platforms, AI/ML, analytics, cloud integration patterns, connectors, workflow systems and marketplace consumption architectures. Experience launching production‐hardened joint solutions with hyperscalers and GSIs with measurable revenue ...

that improve efficiency, decision-making and service delivery. Key responsibilities Build, operate and maintain AI development and production environments using Azure services, including AI, ML and GenAI workloads. Design and manage CI/CD and MLOps pipelines to support model development, deployment, monitoring and lifecycle management. Provision and secure cloud … environments using Infrastructure as Code, with a strong focus on automation, compliance and best practice. Develop and integrate AI applications and services, including classical ML, NLP, RAG and generative AI solutions. Support experimentation and proof-of-concept work through secure AI sandboxes and evaluation of emerging tools and platforms. Monitor ...

with ontologies, semantic data platforms, and AI agents. Design decision systems - Go beyond modelling to architect end-to-end decision systems combining data pipelines, ML models, business rules, semantic layers and AI agents, all embedded in real workflows and operational systems. Grow the business - Drive new client relationships and expand … decision science, data science, quantitative modelling, or operations research. Proven track record applying models in live business decision environments. Strong fluency in Python, modern ML tools, and decision optimisation frameworks. Deep understanding of statistical modelling and machine learning with experience deploying models into production-scale systems. Beneficial: pricing ...

with ontologies, semantic data platforms, and AI agents. Design decision systems - Go beyond modelling to architect end-to-end decision systems combining data pipelines, ML models, business rules, semantic layers and AI agents, all embedded in real workflows and operational systems. Grow the business - Drive new client relationships and expand … decision science, data science, quantitative modelling, or operations research. Proven track record applying models in live business decision environments. Strong fluency in Python, modern ML tools, and decision optimisation frameworks. Deep understanding of statistical modelling and machine learning with experience deploying models into production-scale systems. Beneficial: pricing ...