701 to 725 of 1,868 Remote Machine Learning Jobs

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

supporting their Commodities front office trading business. You'll work with business stakeholders to understand requirements, design and build robust data pipelines and deliver end-to-end analytics and ML/AI capabilities. This is a long-term contract role. The following skills/experience is essential: Strong expertise in Python, PySpark, and SQL Extensive hands-on experience with Databricks … Familiarity with Data Science and Machine Learning frameworks Previously worked in Financial Services Trading environment Background in DevOps and Infrastructure as Code (IaC) Commodities industry experience is highly desirable Rate: Up to £700/day Duration: 12 months + Location: London (good work from home options available) If you are interested in this Senior Data Engineer position and More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

work at the intersection of machine learning and cloud infrastructure, ensuring our models run efficiently, reliably, and cost-effectively at scale. Key Responsibilities Design, deploy, and manage ML infrastructure on AWS (SageMaker) and Kubernetes Build scalable pipelines for LLM and video generation models Optimise model inference, latency, and costs Implement monitoring, logging, and alerting for production systems Collaborate … with ML teams to productionize new models Manage compute scaling, security, and compliance Develop automation and tooling for smoother ML operations Skills & Experience Strong Python skills and production coding experience Proven experience deploying/scaling LLMs or generative AI models Expertise in AWS SageMaker, Kubernetes, and CI/CD (Terraform/CloudFormation) Solid understanding of ML serving, optimisation, and cloud More ❯

who are looking for a contract Data Architect to join an AI programme. This individual will be responsible for designing and implementing modern data architectures that enable advanced analytics, machine learning and AI capabilities. … Data Architect, key responsibilities: Design and implement high-performance data architectures to support AI and analytics workloads Develop and maintain data models and governance frameworks that enable AI and ML systems Partner with Data Scientists, ML Engineers, and Software Engineers to deliver AI Lead data platform modernisation efforts Define data standards, metadata, lineage and quality frameworks Collaborate with stakeholders to More ❯

who are looking for a contract Data Architect to join an AI programme. This individual will be responsible for designing and implementing modern data architectures that enable advanced analytics, machine learning and AI capabilities. … Data Architect, key responsibilities: Design and implement high-performance data architectures to support AI and analytics workloads Develop and maintain data models and governance frameworks that enable AI and ML systems Partner with Data Scientists, ML Engineers, and Software Engineers to deliver AI Lead data platform modernisation efforts Define data standards, metadata, lineage and quality frameworks Collaborate with stakeholders to More ❯

is seeking individuals who thrive in building out a department, and processes while helping scale out a newer function within the greater organization. This requires a proactive approach to learning and a self-starter mindset especially when faced with ambiguity. Technical Expertise This role requires a strong technical foundation. Ideal candidates should have prior experience working with APIs, data … complex data structures and prescribe best practices to optimize them Familiarity with data science and statistics principles, A/B testing methodologies and analytics Ability to explain AI and Machine Learning concepts to both technical and non-technical audiences This role is ideal for someone who can bridge the gap between engineering and business teams, ensuring seamless communication … the ability to articulate these concepts to both technical and non-technical audiences and the ability to tie these principles to business outcomes Experience with ecommerce ecosystems, AI/ML, JavaScript Passion for innovative technology, technical sales, value based conversations Ability to manage several projects simultaneously, work with different salespeople, and support other solutions team colleagues where needed Comfort working More ❯

detection strategy Provide authoritative subject matter expertise on wholesale payment fraud typologies Drive the end-to-end design of the fraud detection services, encompassing data ingestion, rule engine logic, machine learning models, alert generation, case management, and integration points with existing Citi platforms and external systems. Lead and influence cross-functional teams across Technology, Operations, Product, Legal, Compliance … from you Significant experience in fraud prevention, risk management within a large financial institution. Deep understanding of wholesale payment products and associated fraud typologies. Experience working with AI/ML based monitoring systems and models, with an understanding of associated monitoring operations, oversight and model risk management activities Proven track record of leading complex, end-to-end projects in a … Private medical insurance packages to suit your personal circumstances Employee Assistance Program Pension Plan Paid Parental Leave Special discounts for employees, family, and friends Access to an array of learning and development resourcesAlongside these benefits Citi is committed to ensuring our workplace is where everyone feels comfortable coming to work as their whole self every day. We want the More ❯

reimagining how AI can transform client delivery, knowledge management, and operational excellence across a global firm. Work directly with data scientists and AI engineers on enterprise-scale AI and machine learning products. Build production-ready applications that leverage Generative AI and Large Language Models (LLMs) . Hybrid flexibility: 3 days per week in either London, Cambridge, or Bristol … based solutions and managing DevOps processes for seamless deployment. Working in an agile team , contributing to sprints, backlog refinement, and continuous improvement. Staying up to date with AI/ML and LLM trends to bring innovative ideas into production. Ensuring code quality through testing, documentation, and peer review. 4+ years experience building enterprise-grade applications. Strong backend skills in Python More ❯

truth" network data from the integration layer to our core AI Service Bus (Apache Kafka). Cross-functional Collaboration Work closely with the Scam Detection Service and AI/ML teams to define the feature vectors and data payloads needed from the network to power our proprietary machine learning models. Partner with product and leadership to define the More ❯

truth" network data from the integration layer to our core AI Service Bus (Apache Kafka). Cross-functional Collaboration Work closely with the Scam Detection Service and AI/ML teams to define the feature vectors and data payloads needed from the network to power our proprietary machine learning models. Partner with product and leadership to define the More ❯