Senior Machine Learning Engineer (AI)

TL;DR

Senior Machine Learning Engineer (AI): Developing and deploying scalable infrastructure for deep learning pipelines to process massive-scale genomic data with an accent on distributed computing, hardware optimization, and model performance. Focus on building robust, reproducible ML workflows in a cloud environment to accelerate cancer detection research.

Location: Must be based in the US. This is a hybrid role based in Brisbane, California (2-3 days per week in office) or remote.

Salary: $161,925 - $227,325

Company

hirify.global is a biotechnology company dedicated to reducing cancer mortality through accessible early detection using advanced machine learning and genomic data.

What you will do

• Implement and refine deep learning pipelines on distributed computing platforms to enhance training speed and efficiency.
• Collaborate with ML scientists and software engineers to align infrastructure development with scientific research goals.
• Monitor, evaluate, and optimize model training pipelines for performance and scalability.
• Develop and maintain robust, reproducible pipelines to ensure consistency and accuracy in research results.
• Drive performance improvements through profiling, benchmarking, and debugging distributed systems.
• Facilitate communication between engineering and scientific teams by documenting and sharing best practices.

Requirements

• Must be based in the US.
• MS or equivalent experience in a quantitative field with an emphasis on AI/ML theory.
• 5+ years of industry experience developing AI/ML software engineering pipelines.
• Proficiency in Python or other general-purpose languages like Java, Julia, or C++.
• Strong knowledge of ML/DL fundamentals and frameworks such as PyTorch, TensorFlow, or Jax.
• Experience with cloud platforms (AWS, GCP, or Azure) and containerization/orchestration tools like Docker and Kubernetes.

Nice to have

• Experience with large-scale genomics or biological datasets.
• Knowledge of GPU/Accelerator programming (CUDA, Triton, XLA).
• Experience with infrastructure-as-code and MLOps best practices.
• Contributions to relevant open-source DL projects.

Culture & Benefits

• Competitive base salary with equity and cash bonuses.
• Comprehensive medical, financial, and other benefits.
• Interdisciplinary R&D environment focused on high-impact cancer research.
• Commitment to diversity and equal opportunity employment.