Senior Machine Learning Engineer

Freenome
Brisbane
Workplace: HybridFull timeUSD 161,925 - 227,325 annuallyFunction: Data Science & Machine LearningExperience: 5+ yearsEducation: mastersSkills: ["Cross-functional collaboration","Communication across disciplines","Continuous learning"]

Build and deploy deep learning infrastructure for large-scale genomic models, enabling distributed training pipelines and reliable model operations in cloud environments. Collaborate with ML scientists, computational biologists, and software engineers to align pipeline development with scientific goals. Continuously monitor, evaluate, and optimize training performance and scalability through profiling, benchmarking, caching, and debugging distributed systems. Document best practices and help accelerate state-of-the-art ML/AI model development.

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FursaFursa
Freenome
Freenome
1 month ago

Senior Machine Learning Engineer

✓ Verified Job

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

Build and deploy deep learning infrastructure for large-scale genomic models, enabling distributed training pipelines and reliable model operations in cloud environments. Collaborate with ML scientists, computational biologists, and software engineers to align pipeline development with scientific goals. Continuously monitor, evaluate, and optimize training performance and scalability through profiling, benchmarking, caching, and debugging distributed systems. Document best practices and help accelerate state-of-the-art ML/AI model development.
Location: Brisbane
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Implement and refine distributed deep learning pipelines for training, data handling, model management, and inference.
  • •Partner with ML scientists and software engineers to ensure pipelines match scientific goals and operational needs.
  • •Monitor, evaluate, and optimize training pipelines for performance and scalability.
  • •Maintain robust, reproducible pipelines to ensure consistent and accurate results.
  • •Drive performance improvements via profiling, optimization, benchmarking, caching, and debugging distributed systems; document best practices.

Pay and Benefits

Salary: USD 161,925 - 227,325 annually
Equity and Bonus:Equity
Perks:Health InsuranceEquityAnnual Bonus

Key Requirements

  • •MS or equivalent in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Software Engineering) with emphasis on AI/ML theory and/or development.
  • •5+ years post-MS industry experience developing AI/ML software engineering pipelines.
  • •Proficiency in a general-purpose programming language (Python preferred; also Java, Julia, C/C++).
  • •Hands-on experience with ML/DL fundamentals and frameworks such as PyTorch, TensorFlow, Jax, or Scikit-learn.
  • •Experience with scalable distributed computing and cloud deployment, including platforms like Ray/DeepSpeed and tools such as Docker/Kubernetes.
Experience:5+ yearsGenomicsAI/MLDeep learningLLMs
Education:Master's
Skills:Cross-functional collaborationCommunication across disciplinesContinuous learning
Languages:English
Tech Stack:PythonJavaJuliaCC++PyTorchTensorFlowJaxScikit-learnRayDeepSpeedTensorBoardWandbMLflowAWSGoogle CloudAzureDockerKubernetesHDFS

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