AI Engineer
Summary
AI Engineer building and scaling end-to-end AI systems—LLMs, generative AI, recommendation systems—from experimentation through production deployment using Python, C++, and deep learning frameworks at DIDI Mobility.
About the Role
We are seeking a talented AI Engineer to join our team and help build and scale the artificial intelligence systems that power our products and platforms. In this role, you'll work at the intersection of applied AI research and production engineering, translating cutting-edge techniques into reliable, high-impact systems that deliver real-world value. You will be responsible for delivering end-to-end AI solutions—from experimentation through deployment and monitoring—that solve business-critical problems using a mix of classical ML, deep learning, and generative AI.
What You'll Do
Design, build, and deploy AI-driven solutions—spanning large language models, generative AI, recommendation systems, and intelligent automation—that directly shape user and business-facing products
Develop and optimise large-scale AI models from prototype through production deployment, including model training pipelines, inference infrastructure, and feature engineering frameworks
Establish and maintain robust evaluation frameworks, automated testing, and monitoring pipelines to ensure reliability and quality of AI systems in production
Own the technical design of AI components and systems, evaluating architectural trade-offs to meet well-defined product and business requirements
Collaborate with product managers, data scientists, and engineering teams to translate AI research advances into production-ready features with measurable user impact
Adopt best practices in ML development lifecycle—data versioning, model training, evaluation, monitoring, and responsible AI
Instrument AI systems with telemetry, design experiments to validate model hypotheses, and make data-informed decisions
What You'll Need
Bachelor’s Degree or above in Computer Science, AI, or a related field, with 3+ years of experience building and deploying ML/AI systems
Strong proficiency in Python and C++; solid grasp of algorithms, data structures, and software engineering principles
Hands‑on experience with deep learning frameworks (PyTorch or TensorFlow) and end‑to‑end ML pipelines (data processing, training, evaluation, serving)
Proven ability to translate business requirements into technical solutions and deliver impactful projects
Excellent collaboration and communication skills to work effectively with cross‑functional teams