Top Tech Jobs & Startup Jobs

Support product discovery, user research and usability testing; create low-fidelity wireframes, user flows and interface designs; prepare and deliver design assets; collaborate with Product and Engineering in Agile squads; contribute to design systems, accessibility and stakeholder communication while learning tools and processes.

Provide technical support and troubleshooting for ad serving, integrations and reporting. Onboard and test supply/demand partners (OpenRTB, ad tags, deal IDs). Monitor system performance, analyse partner data, recommend optimisations, escalate to engineering, and maintain documentation and training materials.

Produce a high-profile daily sports podcast: book guests, set up outside broadcasts, develop editorial ideas, edit audio on tight deadlines using Adobe Audition, create short-form social content, support cross-show production (including Formula 1), and coordinate promotion with internal teams.

Build and maintain scalable backend APIs and microservices in Python/FastAPI, design data pipelines and Snowflake integrations, enable AI/ML model deployment on cloud (AWS), and drive production delivery and engineering best practices for the Global:IQ intelligence platform.

Build and maintain scalable backend APIs and microservices with Python and FastAPI; develop data engineering pipelines; integrate and optimize data access with Snowflake and AWS; support production deployment of AI/ML features and collaborate across the Global:IQ team to deliver AI-enabled product outcomes.

Lead CX and CRM strategy for Global's consumer digital products. Own lifecycle communications in Braze, design loyalty propositions, run segmented campaigns, measure performance, and manage a team of four while partnering with Product, Data, Marketing and brand teams to improve engagement, retention and loyalty.

Build and maintain scalable, documented analytics data models and reusable datasets. Implement automated data-quality tests, orchestration and CI/CD. Partner with Analytics, Product and Data Science to define common metrics and business logic, improving discoverability and consistency across BI and analytics use cases.

Design, build, and maintain production data pipelines, services and platform capabilities for the Digital Ad Exchange. Collaborate with engineers, analysts and product teams, participate in code review and planning, and operate/support pipelines—investigating failures, improving observability, reliability and data quality.

Build and operate MLOps platform components: pipelines, model registries, deployment, monitoring, drift detection, and retraining. Collaborate with Data Science and Data Engineering to establish reproducible, scalable ML lifecycles, governance, and CI/CD for production ML services, and mentor junior engineers.

Develop and modernize microservices using Java and Spring, build REST/GraphQL APIs, contribute to CI/CD, run services on Kubernetes (EKS), support monitoring with Prometheus/Grafana, collaborate with cross-functional teams, and use AI tools to improve delivery and code quality.