
Senior Machine Learning Engineer
- Beijing
- Permanent
- Full-time
- Identify areas for investigation, translate them to technical problems to be solved, explain solutions to tech and non-tech team members
- Oversee end-to-end small/moderate products/services from design to production rollout
- Define hypotheses, develop necessary tests, experiments, and data analyses to prove or disprove them independently
- Develop, and increase deep learning and machine learning algorithms-including generative AI, Large Language Models (LLMs), and multi-modal models-for real-world impact
- Fine-tune, evaluate, and adapt LLMs (e.g., GPT, Llama, Qwen) and other foundation models using both supervised and reinforcement learning approaches
- Architect agentic AI workflows using modern orchestration frameworks (e.g., LangChain, LlamaIndex, OpenAI Function Calling), including tool integration, chaining, and multi-agent coordination
- Contribute to team's innovation and IP creation
- Keep up with the latest literature in Search / Recommendation, Natural Language Processing/LLMs or Computer Vision
- Master in Computer Science, Electrical/Computer Engineering, Operations Research.
- Hands-on experience in deep learning and AI, with expertise in LLMs including fine-tuning, prompt engineering, and adapting foundation models for downstream tasks
- Demonstrated experience deploying LLMs and other large-scale AI models to production:
- 1+ years of experience serving LLMs and agentic systems in production environments (e.g., TorchServe, Triton, or Ray Serve)
- Knowledge of model compression, quantization, and techniques for optimizing inference latency and cost
- Familiarity with GPU/TPU acceleration and distributed inference architectures
- Experience implementing and maintaining scalable pipelines for data preprocessing, model training, fine-tuning, and automated evaluation
- Proficiency in deep learning frameworks (TensorFlow, PyTorch) and deployment tools (ONNX, tf-serving, TorchServe, Triton Inference Server)
- Solid software engineering skills in Python/Spark; knowledge of GoLang or Rust
- Experience with model versioning, CI/CD for ML, containerization (e.g., Docker), and cloud-based deployment (AWS, GCP, Azure)
- We have your back with Term Life Insurance and comprehensive Medical Insurance.
- With GrabFlex, create a benefits package that suits your needs and aspirations.
- Celebrate moments that matter in life with loved ones through Parental and Birthday leave, and give back to your communities through Love-all-Serve-all (LASA) volunteering leave
- We have a confidential Grabber Assistance Programme to guide and uplift you and your loved ones through life's challenges.
- Balancing personal commitments and life's demands are made easier with our FlexWork arrangements such as differentiated hours