Job Description
Join QuantumLeap Technologies as a Senior Machine Learning Engineer and pioneer the future of AI-driven innovation. We're revolutionizing healthcare diagnostics through cutting-edge neural networks and predictive analytics. In this pivotal role, you'll architect scalable ML pipelines that process genomic data with unprecedented precision, directly impacting patient outcomes worldwide. Our state-of-the-art lab collaborates with Stanford Medicine and UCSF, offering unparalleled access to real-world clinical datasets.
We foster a culture where curiosity meets execution—your ideas will shape products used by millions. Enjoy flexible work arrangements, unlimited learning stipends, and equity in a Series C-funded startup disrupting the $500B healthcare AI market. This hybrid role requires 2 days/week in our Mission Bay campus to maximize collaborative innovation.
Responsibilities
- Design and implement production-grade ML models for medical image analysis achieving >95% diagnostic accuracy
- Lead end-to-end ML pipeline development from data ingestion to deployment on AWS/GCP
- Collaborate with cross-functional teams (clinical, engineering, product) to translate research into clinical applications
- Optimize deep learning architectures for real-time inference in medical device environments
- Contribute 2-3 patents/year for novel ML techniques in healthcare diagnostics
- Mentor junior engineers through technical reviews and innovation workshops
- Stay current with latest research papers in Nature Medicine and NeurIPS conferences
Qualifications
- MS/PhD in Computer Science, Mathematics, or related field with 5+ years ML engineering experience
- Proven expertise in PyTorch/TensorFlow with 3+ deployed production models handling terabyte-scale data
- Strong foundation in Bayesian statistics and probabilistic graphical models
- Experience with healthcare data (DICOM, FHIR) and regulatory compliance (HIPAA, FDA guidelines)
- Proficiency in MLOps tools (Kubernetes, MLflow, Kubeflow) for model lifecycle management
- Publication record at top-tier conferences (NeurIPS, ICML, CVPR) or equivalent industry impact
- Ability to translate complex ML concepts into actionable business strategies