Machine Learning Engineer

Responsibilities

• Build robust data pipelines that mine the Internet at scale and generate millions of synthetic text examples for training detection models.
• Manage distributed infrastructure for multi-GPU LLM training.
• Profile and optimize training and inference code.
• Deploy efficient inference pipelines for serving LLMs at scale.
• Contribute to research efforts, ideas, innovations, and publications.

Requirements

• Bachelor's or master's degree in Computer Science or a related area.
• Strong programming skills in Python and modern machine learning frameworks.
• Excellent understanding of transformers and LLM fundamentals.
• Comfort working across research and engineering boundaries.
• Preferred experience with NVIDIA GPU programming and CUDA.
• Preferred experience with distributed training frameworks such as DeepSpeed, FSDL, and Ray.
• Preferred experience with inference frameworks such as vLLM.
• Preferred experience with large-scale data processing using Spark or Beam and orchestration using Airflow.
• Preferred experience with MLOps and experiment tracking.
• Preferred experience with DevOps tools and cloud-based infrastructure such as AWS or GCP.

Benefits

• Fully in-person role in Downtown Brooklyn, New York.
• Meaningful ownership over the company’s technical and strategic direction.
• Opportunity to collaborate with researchers and contribute to published research.