ML Engineer

Responsibilities

• Profile inference bottlenecks in selected biological models
• Implement and test optimization techniques such as quantization, pruning, and distillation
• Explore efficient attention and architecture-level improvements
• Build and benchmark optimized inference pipelines
• Evaluate speed, memory, and accuracy trade-offs
• Write clean, well-documented experimental code
• Share results and practical deployment recommendations

Requirements

• Enrollment in or completion of a degree in computer science, AI, or a related field
• Strong knowledge of computer science and machine learning fundamentals
• Experience with Python and familiarity with deep learning frameworks
• Ability to write clean, efficient code
• Strong problem-solving skills and a willingness to learn quickly
• Interest in life sciences

Preferred Qualifications

• Familiarity with large language models and transformer architectures
• Experience profiling GPU workloads and optimizing deep learning systems
• Experience with model compression techniques
• Experience working with large-scale models or distributed inference
• Contributions to open-source ML projects

Benefits

• Competitive salary and comprehensive benefits package
• Mentorship from experienced AI, ML, and cloud infrastructure professionals
• Hands-on experience with real customer workloads and production systems
• Opportunities for professional growth within Nebius
• Opportunity to be considered for a full-time role after the Early Talent Program

About the Company

Nebius is leading a new era in cloud infrastructure for the global AI economy, building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment.