Staff Machine Learning Scientist (AI)

TL;DR

Staff Machine Learning Scientist (AI): Developing advanced algorithms for early, blood-based cancer detection with an accent on deep learning methods and molecular signal identification. Focus on building robust models, driving independent research, and collaborating with computational biologists to transform cancer landscape.

Location: Remote or Hybrid in Brisbane, California (2-3 days per week in office)

Salary: $199,675 - $283,500

Company

hirify.global is an innovative biotechnology company dedicated to changing the landscape of cancer detection through advanced molecular signal analysis.

What you will do

• Independently pursue cutting-edge AI research applied to biological problems like genomics and immunology.
• Develop and fine-tune models to identify biological changes associated with diseases.
• Ensure model high accuracy and robustness for generalization across new data.
• Apply interpretability techniques to derive biological insights and potential mechanisms from models.
• Collaborate with ML Engineering partners to optimize computational infrastructure for training and iteration.

Requirements

• PhD or equivalent research experience in a quantitative field such as Computer Science, Statistics, or Computational Biology.
• 6+ years of post-PhD experience in industry achieving impactful results with modeling techniques.
• Extensive expertise in applied machine learning, deep learning, and complex data modeling.
• Proficiency in a general-purpose programming language such as Python or C++.
• Experience with ML frameworks like Pytorch, Tensorflow, or Jax and platforms like Hugging Face.
• Ability to communicate complex findings effectively across cross-functional scientific teams.

Nice to have

• Deep domain experience in computational biology, genomics, or proteomics.
• Experience building deep learning models for genomic data and DNA foundation models.
• Familiarity with NGS data analysis and bioinformatic pipelines.
• Experience with cloud computing environments like GCP, Azure, or AWS.
• Background in production software engineering, including regression testing and version control.

Culture & Benefits

• Comprehensive medical, financial, and other health benefits.
• Equity eligibility and cash bonus programs.
• Opportunity to influence the growth of an organization dedicated to cancer research.
• Collaborative, cross-functional environment working with computational and molecular biologists.