ML Engineer (Life Sciences)

TL;DR

ML Engineer (Life Sciences): Optimizing biological AI models for faster and more efficient inference with an accent on model compression and architectural improvements. Focus on profiling bottlenecks, implementing quantization/pruning techniques, and building high-performance inference pipelines for research and production.

Location: Must be based in Amsterdam, Netherlands

Company

hirify.global is a global cloud platform building the next generation of infrastructure to support the AI economy.

What you will do

• Profile inference bottlenecks in biological AI models like protein folding and design architectures.
• Implement and test model optimization techniques including quantization, pruning, and distillation.
• Explore efficient attention mechanisms and architecture-level improvements.
• Build and benchmark optimized inference pipelines for real-world production use.
• Evaluate critical trade-offs between model speed, memory usage, and biological accuracy.
• Document experimental code and share deployment recommendations with the team.

Requirements

• Current University student, recent graduate, or early-career specialist.
• Strong foundation in computer science and machine learning principles.
• Proficiency in Python and familiarity with deep learning frameworks.
• Ability to write clean, efficient, and well-documented experimental code.
• Strong problem-solving skills with a high aptitude for learning.
• Must be able to work onsite in Amsterdam.

Nice to have

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

Culture & Benefits

• Mentorship from experienced leaders in AI, machine learning, and cloud infrastructure.
• Hands-on experience with production-scale systems and customer workloads.
• Dynamic and collaborative work environment focused on innovation.
• Competitive salary and comprehensive benefits package.
• Potential opportunity to be considered for a full-time role following the program.