Principal ML Research Engineer (AI)

TL;DR

Principal ML Research Engineer (AI/Cell Biology): Building and operating the engineering platform for cell- and tissue-scale biology with an accent on domain data curation, specialist-model serving, and agentic infrastructure. Focus on creating a composable system of specialist models and evaluation harnesses to accelerate autonomous scientific discovery.

Location: San Francisco, CA, USA

Company

hirify.global is building Scientific Superintelligence™ to autonomously execute the scientific method and accelerate discovery across medicine, materials, and energy.

What you will do

• Build and operate a domain data platform for multi-modal scientific data including single-cell, multi-omics, and imaging.
• Develop a shared specialist-model serving and fine-tuning stack for cell- and tissue-resolution biology models.
• Implement agentic infrastructure for rollout generation, tool orchestration, and rubric grading.
• Create a cross-program evaluation harness to connect internal metrics to the broader scientific evaluation suite.
• Partner with central AI and Data platform teams to extend core infrastructure for cell-biology-specific needs.
• Establish engineering standards for code quality, MLOps, and reproducibility while mentoring research engineers.

Requirements

• Advanced degree (MS or PhD) in Computer Science, Machine Learning, or a related field.
• 8+ years of ML platform, infrastructure, or research-engineering experience with a record of shipping production ML systems.
• Deep experience designing data pipelines for high-dimensional multi-modal scientific data.
• Strong fluency in PyTorch, Python, containers, Kubernetes, and CI/CD.
• Demonstrated experience with agentic, active-learning, or closed-loop systems orchestrating scientific tools.
• Must be based in San Francisco, CA, USA.

Nice to have

• Experience composing specialist biology models into multi-step reasoning systems.
• Experience with Lab-in-the-Loop workflows where predictions drive experimental decisions.
• Contributions to open-source ML platform tooling or biological modeling libraries.
• Prior experience as a founding engineer or technical lead on a new team.

Culture & Benefits

• Fast-paced startup environment operating with high velocity and grit.
• Opportunity to act as a founding engineering leader on a new, high-impact team.
• Work on problems of historic importance in the frontier of AI for science.
• Commitment to equal employment opportunity and a diverse work environment.