Senior Machine Learning Engineer - Orchestration

What you'll do

• Optimize distributed resource scheduling, autoscaling, resource allocation, and workload placement across clusters, data centers, regions, and clouds.
• Build distributed training runtimes and computing APIs for large recommendation models and optimize training-system usability and diagnosability.
• Develop online inference and orchestration architecture for recommendation systems and improve MLops workflows.

What they ask for

• Bachelor's degree or above in Computer Science or a similar field of study.
• 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 principles and experience 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 open-source training orchestration systems such as veRL, VLLM, Ray, or TFX.

Tools

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

AI focus

Builds and optimizes machine-learning infrastructure for large-scale recommendation and advertising models, including distributed training, inference, resource orchestration, and autoscaling.