Senior Machine Learning Engineer - Orchestration

What you'll do

• Optimize distributed scheduling, autoscaling, resource allocation, and workload placement across clusters, data centers, regions, and clouds.
• Build distributed training runtimes and computing APIs for ultra-large recommendation models and emerging research paradigms.
• Develop robust inference architecture and improve platform diagnosability, usability, and MLops workflows.

What they ask for

• Bachelor's degree or above in Computer Science or a similar field.
• At least 5 years of experience and proficiency in Go or Python in a Linux environment, with strong hands-on coding skills.
• Practical experience with open-source distributed scheduling frameworks and Machine Learning systems.
• Knowledge of distributed systems, including participation in designing, developing, and maintaining large-scale distributed systems.

Nice to have

• Familiarity with PyTorch or TensorFlow.
• Experience in AI Infrastructure, HW/SW Co-Design, High Performance Computing, ML Hardware Architecture, or training orchestration systems such as veRL, VLLM, Ray, or TFX.

Tools

Go, Python, Linux, Kubernetes (K8S), Yarn, Flink, MapReduce, Mesos

AI focus

Develops infrastructure for machine learning recommendation and advertising systems, including distributed training and inference, resource orchestration, and support for RL, finetuning, and distillation.