Senior Machine Learning Engineer
Freenome · Remote
About this role
**About this opportunity:** Freenome is seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team within the Computational Science department. The ideal candidate has strong expertise in designing and building deep learning pipelines and creating reliable, scalable AI/ML systems in cloud environments. The MLS team develops DL models using massive-scale genomic data. You'll be responsible for developing and deploying infrastructure to support DL model development: enabling distributed DL pipelines, optimizing hardware utilization, and performing model optimizations. You'll work collaboratively with ML scientists, computational biologists, and software engineers to accelerate state-of-the-art ML/AI models. Reports to: Director of Machine Learning Science Location: Hybrid (Brisbane, CA HQ, 2-3 days/week) or Remote **What you'll do:** • Implement and refine DL pipelines on distributed computing platforms • Collaborate with ML scientists and engineers to align pipelines with scientific goals • Monitor, evaluate, and optimize DL training pipelines for performance and scalability • Stay current with latest AI/ML advancements and adapt new tools as needed • Develop robust, reproducible DL pipelines ensuring reliable execution • Drive performance improvements through profiling, optimization, and benchmarking • Bridge engineering and scientific teams, sharing best practices **Must haves:** • MS or equivalent in Computer Science, Statistics, Mathematics, or related field • 5+ years post-MS industry experience developing AI/ML software engineering pipelines • Proficiency in Python (preferred), Java, Julia, C, or C++ • Strong ML/DL fundamentals with hands-on experience (PyTorch, TensorFlow, JAX, Scikit-learn) • In-depth knowledge of distributed computing platforms (Ray, DeepSpeed) • Experience with cloud platforms (AWS, Google Cloud, Azure) • Proficiency with containerization (Docker) and orchestration (Kubernetes) • Proven track record optimizing DL model training workflows • Experience managing large datasets and efficient data processing • Proficiency with Git and CI/CD practices • Expertise building large-scale ML frameworks in scientific environments • Excellent cross-functional communication skills **Nice to haves:** • Experience with large-scale genomics or biological datasets • Experience with multimodal datasets • GPU/Accelerator programming (CUDA, Triton, XLA) • Infrastructure-as-code and configuration management • MLOps and ML infrastructure best practices • Strong open-source contributions **Compensation & Benefits:** Base salary range: $161,925 - $227,325 + equity, bonuses, and comprehensive benefits
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