Staff Machine Learning Scientist

Freenome
Brisbane
Workplace: HybridFull timeUSD 199,675 - 283,500Function: Data Science & Machine LearningExperience: 6+ yearsEducation: phdSkills: ["Cross-functional collaboration","Communication","Independent research","Innovation","Iterative experimentation"]

Develop AI/ML algorithms for early, blood-based cancer detection, building on ML/DL and statistical methods to identify molecular signals from blood. Conduct independent, cutting-edge research applied to biological problems (cancer, genomics, computational biology, immunology), improving model accuracy and generalization. Use interpretability techniques to surface underlying biological mechanisms and partner with ML Engineering to support training and iteration infrastructure in a cross-functional environment.

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FursaFursa
Freenome
Freenome
1 month ago

Staff Machine Learning Scientist

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live
Reposted: similar role first listed 10 months ago

Job Summary

Develop AI/ML algorithms for early, blood-based cancer detection, building on ML/DL and statistical methods to identify molecular signals from blood. Conduct independent, cutting-edge research applied to biological problems (cancer, genomics, computational biology, immunology), improving model accuracy and generalization. Use interpretability techniques to surface underlying biological mechanisms and partner with ML Engineering to support training and iteration infrastructure in a cross-functional environment.
Location: Brisbane
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Independently pursue cutting-edge AI research applied to biological problems, including cancer research, genomics, computational biology, and immunology.
  • •Build or fine-tune ML/DL models to identify biological changes resulting from disease and molecular signals from blood.
  • •Develop models that achieve high accuracy and robust generalization to new data.
  • •Apply interpretability techniques to understand underlying model signals and suggest potential biological mechanisms.
  • •Partner with ML Engineering to ensure computational infrastructure supports optimal model training and iteration.

Pay and Benefits

Salary: USD 199,675 - 283,500
Perks:Equity

Key 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 postdoc or post-PhD industry experience delivering impactful results using relevant modeling techniques.
  • •Demonstrated independent research impact through publications or industry achievements in applied machine learning, deep learning, and complex data modeling.
  • •Strong practical/theoretical understanding of fundamental ML models (e.g., generalized linear models, kernel machines, decision trees/forests, neural networks, boosting, model aggregation).
  • •Strong practical/theoretical understanding of DL models (including large language models/foundation models) and experience with supervised, self-supervised, and contrastive learning.
Experience:6+ yearsComputational biologyGenomicsBioinformatics
Education:PhD / Doctorate
Skills:Cross-functional collaborationCommunicationIndependent researchInnovationIterative experimentation
Languages:English
Tech Stack:PythonRJavaCC++PyTorchTensorFlowJAXHugging FaceTensorBoardMLflowWeights & BiasesGeneralized linear modelsKernel machinesDecision treesRandom forestsNeural networksBoostingModel aggregationLarge language models

Company Brief

Freenome
Develops blood-based early cancer detection tests by combining cell-free DNA analysis, genomics, and machine learning to identify cancer signals for screening and diagnosis, aiming to enable earlier, noninvasive detection across multiple cancer types.
Industry: Diagnostics
Company Size: Large (251 to 1,000 employees)
Growth: Growth Stage Startup
Headquarters: South San Francisco, United States
Founded: 2014
WebsiteLinkedIn