Staff Machine Learning Scientist

🔥 0 minutes ago

🏄 California – Remote

🏄 California – Remote

💵 $199.7k - $283.5k / year

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

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Freenome

WebsiteLinkedInAll Job Openings

201 - 500 employees

Founded 2014

🏥 Healthcare

🧬 Biotechnology

🤖 Artificial Intelligence

💰 $290M Corporate Round on 2022-01

Healthcare • Biotechnology • Artificial Intelligence

Freenome is a company focused on advancing early cancer detection through the integration of scientific innovation and artificial intelligence. Their platform uses multiomics technology to identify cancer at its most treatable stages, enabling early intervention. The company emphasizes a standard blood draw method for ease of use, aiming to redefine cancer screening. Freenome is driven by a robust clinical research program and is committed to discovering, developing, and validating early cancer detection tests, employing a multidisciplinary team dedicated to pushing the boundaries of what's possible in cancer diagnostics.

📋 Description

• Independently pursue cutting-edge research in AI applied to biological problems, including cancer research, genomics, computational biology, and immunology • Build new models or fine-tune existing models to identify biological changes resulting from disease • Build models that achieve high accuracy and generalize robustly to new data • Apply contemporary interpretability techniques to understand underlying signals and suggest potential biological mechanisms • Collaborate with ML Engineering partners to ensure computational infrastructure supports optimal model training and iteration • Work with computational biologists, molecular biologists, and ML engineers to design and drive research experiments • Develop algorithms for early, blood-based cancer detection tests • Take a mindful, transparent, and humane approach to the work • Report to the Director, Machine Learning Science

🎯 Requirements

• PhD or equivalent research experience with an AI emphasis in a relevant quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics • 6+ years of postdoctoral or post-PhD industry experience achieving impactful results with relevant modeling techniques • Research publications or industry achievements demonstrating independent research in applied machine learning, deep learning, and complex data modeling • Practical and theoretical understanding of generalized linear models, kernel machines, decision trees and forests, neural networks, boosting, and model aggregation • Practical and theoretical understanding of deep learning models such as large language models or other foundation models • Extensive experience with supervised learning, self-supervised learning, and contrastive learning • Proficiency in current state-of-the-art ML/DL approaches and applying them to biological data • Proficiency in a general-purpose programming language such as Python, R, Java, C, or C++ • Proficiency in ML frameworks such as PyTorch, TensorFlow, or JAX, and ML platforms such as Hugging Face • Experience with ML analysis and developer tools such as TensorBoard, MLflow, or Weights & Biases • Ability to communicate across disciplines, work collaboratively, and make progress through experimental iterations • Cross-functional scientific communication and collaboration with software engineers and computational biologists • Passion for innovation and demonstrated initiative in new research areas • Nice to have: domain-specific experience in computational biology, genomics, proteomics, or a related field • Nice to have: experience building DL models for genomic data and knowledge of DNA foundation models • Nice to have: experience in NGS data analysis and bioinformatic pipelines • Nice to have: experience with Docker in GCP, Azure, or AWS • Nice to have: production software engineering experience including automated regression testing, version control, and deployment systems

🏖️ Benefits

• Base salary of $199,675 - $283,500 • Equity • Cash bonuses • Full range of medical, financial, and other benefits depending on the position offered • Equal-opportunity employer that values diversity