🛠 Tech Stack

💼 About This Role

You'll design and optimize high-performance data pipelines for distributed training and storage at a non-profit using AI to decode animal communication. Your work will enable researchers to experiment faster with production-quality reliability, handling diverse species data at scale. You'll collaborate closely with researchers and engineers to make complex AI workflows simple and efficient.

🎯 What You'll Do

• Design and optimize high-performance data pipelines for distributed training and storage
• Build monitoring and visualization tools for tracking data quality and pipeline performance
• Optimize distributed AI workloads for reliability, latency, and efficiency
• Scope and supervise projects for interns, PhD students, and post-docs

📋 Requirements

• 5+ years of backend or infrastructure engineering experience
• Strong Python programming skills
• Experience with distributed systems and cloud platforms (AWS, GCP, Azure)
• Hands-on experience with containerization (Docker, Kubernetes) and infrastructure as code (Terraform)

✨ Nice to Have

• Deep knowledge of training architectures, CUDA programming, or TPU optimization
• Full-stack development experience with frameworks like React
• Experience managing HPC infrastructure with Slurm or Kubernetes clusters

📨 Hiring Process

Initial 30-minute interview, technical screening (two interviews and take home exercise), panel interview, final interview with Chief Scientist.

🚩 Heads Up

• Role includes supervising interns and post-docs, yet titled senior with no mention of management experience in requirements
• Extensive nice-to-have list suggesting unrealistic expectations for a single role
• Mentoring and recruiting responsibilities may distract from core infrastructure work