Ai Sim - Staff Ml Research Engineer (AI)

TL;DR

AI Sim - Staff ML Research Engineer (AI): Architecting, scaling, and optimizing scientific codebases that power Large Quantitative Models (LQMs) with an accent on transitioning high-impact prototypes into robust products. Focus on orchestrating distributed training pipelines on world-class GPU infrastructure and pioneering hardware-level optimizations that push the boundaries of computational chemistry.

Location: Remote (Canada)

Salary: CA$180K – CA$270K

Company

hirify.global is delivering AI solutions that address some of the world's greatest challenges, with Large Quantitative Models (LQMs) powering advances in life sciences, financial services, navigation, cybersecurity, and other sectors.

What you will do

• Architect and scale ML algorithms into high-performing and robust scientific code.
• Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into large-scale simulation frameworks.
• Implement advanced software and hardware optimizations to maximize the efficiency of ML pipelines across distributed cloud GPU environments.
• Drive software through the entire product lifecycle, ensuring technical excellence at every stage.

Requirements

• MSc (PhD preferred) in Computer Science, Physics, Chemistry, or a related quantitative field focused on advanced computational methods.
• 5+ years industry experience developing productionized software in professional teams.
• Proven experience training and optimizing large-scale ML pipelines on distributed cloud GPUs (e.g. PyTorch, TensorFlow).
• Deep familiarity with agentic coding tools (e.g. Claude code, Codex).
• Experience supporting models in external-facing products, demonstrating the ability to bridge the gap between "research code" and "product code".

Nice to have

• Direct experience in biopharma or training leading-edge affinity, structure-prediction, or generative chemistry models.
• A history of developing and launching successful commercial software products within a professional engineering team.
• Familiarity with MLOps practices on major cloud platforms to support automated scaling and model monitoring.
• Experience working in interdisciplinary environments where AI intersects with physical or biological sciences.

Culture & Benefits

• Competitive base salary, performance-based incentives or bonuses, and equity participation.
• Comprehensive medical, dental, and vision coverage, retirement savings with company matching, paid parental leave, and inclusive family-building benefits.
• Flexible paid time off, company-wide seasonal breaks, and support for flexible work arrangements.
• Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs.