ML Engineer - Life Sciences (Early Talent)

Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure.

Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI.

Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.

Biological AI models (protein folding, protein design, and large foundation models) are powerful but heavy and expensive to run. This project focuses on making them faster and more efficient at inference time without significantly hurting biological quality.

You will work on profiling bottlenecks, applying model compression and architectural optimizations, and building efficient inference pipelines. The goal is to make these models practical for real-world research and production use.

• →Profile inference bottlenecks in selected biological models
• →Implement and test optimization techniques (quantization, pruning, 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

• 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

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

Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI 

Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law.

Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. 

If you need accommodations during the application process, please let us know.