with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯
with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯
with cloud platforms like Microsoft Azure or Google Cloud Platform (GCP); familiarity with Databricks is a plus. Comfort working in cloud-based or secure environments, with an interest in MLOps or model deployment. Awareness and practice of responsible AI, data ethics, and governance frameworks. Willingness to explore emerging technologies such as agentic AI, GitHub Copilot, Microsoft Copilot and Copilot Studio. More ❯
areas for improvements and updates. Passionate about work, output and quality. Curious and willing to onward develop and learn in ML/AI area. Desirable Criteria Benefits: Familiarity with MLOps principles Familiarity with Geospatial (GIS) data Familiarity and experience with agile development in delivery Experience in Automation/Testing frameworks Experience of Continuous Integration/Development and Tooling Experience of More ❯
managers who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI. What You’ll Do You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants. You will work on topics … such as descriptive analytics, predictive models (e.g., boosted trees), and large language models (LLMs), particularly for segmentation use cases. Additionally, you will design and deliver products that adhere to MLOps best practices, ensuring they are both maintainable and deployable. By doing so, you will help bring advanced analytics capabilities into one of flagship products, named "Wave". Your work will More ❯
SR2 | Socially Responsible Recruitment | Certified B CorporationTM
teams. Microservices & API Gateways Guide distributed system architectures and internal service integration. Define best practices for service-to-service communication and data management. AI & ML Enablement Set vision for MLOps platforms and streamline machine learning workflows. Enable deployment of traditional and generative AI models into internal platforms. Developer Experience & DevOps Tooling Shape strategy for CI/CD, Infrastructure as Code … teams on internal tooling and shared services. Track record of delivering internal products that boost developer workflows, reliability, or deployment velocity. Hands-on experience with AI/ML platforms, MLOps, and deploying machine learning models into production environments. Core Focus Areas Core Platform Engineering Developer Experience (DevEx/DX) Engineering Productivity DevOps Tooling Observability Solutions Platform as a Service (PaaS More ❯
