AI Engineer, Playable Ads
On-siteTaipei, Taiwan, Taiwan
Taipei, Taiwan, TaiwanOn-siteFull TimeMasters DegreeAI SoftwareMedium
Full TimeMasters DegreeMediumAI Software
Job Summary
Build and operate reliable, scalable ML and generative AI pipelines that power automated content creation, personalization, and optimization across creative formats. Productionize research prototypes by designing service contracts, containerized workers, and asynchronous orchestration with schema validation and end-to-end testing. Apply modern ML including LLMs, VLMs, and agentic tool use to improve creative quality while defining and monitoring quality, latency, and generation-cost metrics. Collaborate with scientists, backend engineers, product managers, and designers to translate business needs into maintainable systems.
Required Qualifications
- Bachelor's or Master's degree in Computer Science, Machine Learning, Electrical Engineering, or a related field—or equivalent practical experience
- 3 or more years of experience building production software or ML systems, with strong computer science fundamentals and a record of writing maintainable, tested code
- Strong Python skills and hands-on experience with PyTorch, TensorFlow, or equivalent ML tooling
- Practical experience taking models, prompts, or data workflows from prototype to production using APIs, containers, batch or stream processing, and cloud infrastructure
- Experience with cloud and ML platform tooling such as Docker, Kubernetes, GCP, CI/CD, workflow orchestrators, message queues, Spark, or OpenTelemetry
- Understanding of production ML concerns including reproducibility, data and model versioning, evaluation, monitoring, failure handling, latency, and cost
- Strong debugging and systems-thinking skills across distributed components such as queues, workers, storage, and external services
- Clear communication and cross-functional collaboration skills; comfortable using AI-assisted development tools responsibly while validating their output
Desired Qualifications
- Experience with generative media, creative optimization, advertising or MarTech, recommendation, or content-generation products
- Experience designing agent tools, feed-back-loop pipelines, rigorous evaluations, or online experiments—and translating research into measurable product impact
- Hands-on experience with generative AI or multimodal systems, such as LLMs, VLMs, image or video generation, RAG, tool use, or agent frameworks
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