Machine Learning Engineer — Distillation

📋 Description

• Design distillation pipelines (teacher–student, self-distillation, multi-teacher)
• Distill foundation models into smaller, faster, cheaper for inference
• Run large-scale training experiments to evaluate quality, latency, cost
• Collaborate with research to translate ideas into production-ready code
• Optimize training and inference performance (memory, throughput, latency)
• Contribute to internal tooling, evaluation frameworks, and experiment tracking

🎯 Requirements

• Strong background in machine learning or deep learning
• Hands-on experience with model distillation (LLMs or other neural networks)
• Understanding of training dynamics, loss functions, and optimization
• Experience with PyTorch (or JAX) and modern ML tooling
• Comfort running experiments on multi-GPU or distributed setups
• Pragmatic mindset: shipping, not just papers

🎁 Benefits

• Work on core model quality and cost efficiency—not side projects
• High ownership and direct impact on product and roadmap
• Small, senior team with strong research + engineering culture
• Competitive compensation + meaningful equity
• Remote-friendly, async-first environment