Top Tech Jobs & Startup Jobs in Singapore

Design, build, and maintain scalable Playwright/TypeScript automation frameworks and reusable test suites. Integrate tests into CI/CD (Jenkins/GitLab CI), perform frontend/backend (white/gray-box) testing, adopt AI-assisted testing and MCP components, collaborate with developers/DevOps, mentor QA engineers, and improve test reliability and reporting.

Lead product feature definition and requirements, coordinate cross-functional teams, collect and analyze customer needs and product metrics, drive data-driven product decisions, competitor analysis, and establish pricing and licensing models.

The Partner Growth Manager will drive partner growth in Singapore and APAC, focusing on recruitment, activation, and revenue generation through partnership strategies and collaboration with internal teams.

Design and develop learning experiences that translate complex technical and operational knowledge into clear, engaging training. Partner with SMEs, product, and engineering to identify needs, structure curricula, create e-learning/video/guides/assessments, apply instructional design models, measure effectiveness, and iterate programs.

Develop and review C# code, build serverless microservice APIs, write unit tests, integrate customer data, assist DevOps with build/deployment and troubleshoot complex product issues.

Perform hands-on applied research across the product lifecycle: survey literature, design and run experiments, analyze results, and deliver working proof-of-concept code for ML/AI education features, collaborating with research scientists, ML engineers, and product teams to integrate validated approaches.

Designs and maintains CI/CD pipelines, model deployment and rollback workflows, monitoring and observability for ML in production, and manages model lifecycle with MLflow while automating infrastructure and partnering with ML and platform teams.

Define and pursue a research agenda that produces ship-ready AI/quantum proof-of-concept code for education products. Design and run experiments, interpret results, convert validated findings into production-ready code, mentor research associates, and collaborate with ML engineers and leadership to measure product impact.

Own the end-to-end analytics lifecycle: define measurement frameworks, build and maintain data pipelines and dashboards, analyze product/behavioural/model data, support experiment/A-B test design, ensure data quality, and communicate insights to influence product and model decisions.