Senior Machine Learning Scientist (AI)

TL;DR

Senior Machine Learning Scientist (AI): Developing and optimizing early cancer detection algorithms using blood-based biomarkers with an accent on deep learning and complex biological data modeling. Focus on building robust, high-accuracy models and collaborating with computational biologists to drive experimental research in a cross-functional environment.

Location: Must be based in the US. Hybrid role based in Brisbane, CA (2-3 days per week in office) or remote.

Salary: $173,775–$246,750

Company

hirify.global is an innovative healthcare company dedicated to changing the landscape of cancer detection through early, blood-based diagnostic tests powered by advanced machine learning.

What you will do

• Independently conduct cutting-edge research in AI applied to genomics, immunology, and oncology.
• Build and fine-tune machine learning and deep learning models to identify biological signals related to disease.
• Optimize models for high accuracy and robustness to ensure generalization to new, diverse datasets.
• Implement interpretability techniques to derive biological insights from identified model signals.
• Partner with ML engineers to ensure scalable computational infrastructure for model training and iteration.

Requirements

• PhD or equivalent research experience in a quantitative field such as Computer Science, Statistics, Mathematics, or Computational Biology.
• 3+ years of post-PhD industry experience delivering impactful modeling results.
• Demonstrated expertise in applied machine learning, deep learning, and complex data modeling.
• Proficiency in Python or other general-purpose programming languages and ML frameworks like PyTorch, TensorFlow, or JAX.
• Understanding of both fundamental ML models and state-of-the-art deep learning architectures.
• Ability to collaborate across disciplines and communicate complex technical concepts effectively.

Nice to have

• Deep domain experience in computational biology, genomics, or proteomics.
• Experience building deep learning models for genomic data, including DNA foundation models.
• Familiarity with cloud-based containerized environments like Docker, GCP, Azure, or AWS.
• Experience in production software environments with version control and automated testing.

Culture & Benefits

• Comprehensive medical, financial, and insurance benefits.
• Equity eligibility and cash bonuses.
• Inclusive and equal-opportunity work environment.
• Exposure to cutting-edge research at the intersection of AI and biology.