Description

You will build and productionize ML infrastructure to support training, evaluation, and deployment of large language models.

This role is on-site.

Responsibilities

• Design, build, and optimize scalable machine learning infrastructure for LLM training, evaluation, and deployment.
• Build abstractions to automate steps across various ML workflows.
• Collaborate with engineering, data analytics, and ML teams to build new features.
• Drive best practices in ML and data engineering through your experience.

Required Skills

• 5+ years of industry experience in Machine Learning, Infrastructure, or related fields.
• Experience building and scaling end-to-end machine learning systems.
• Expertise in Python and experience with performant languages like C++ or Golang.
• Experience with deep learning frameworks such as PyTorch or Huggingface.
• Experience with LLM serving frameworks such as vLLM or TensorRT-LLM.
• Experience building scalable microservices and ETL pipelines.
• Bachelor's in Computer Science, Computer Engineering, Mathematics, or equivalent field.

Preferred Skills

• Experience with ML Inference optimization using TensorRT.
• Experience with distributed training frameworks such as Deepspeed.

Key Skills

Education

Any Graduate