Staff Machine Learning Engineer

Our ML team builds the core intelligence layer of Curely AI — the models that power clinical risk stratification, NLP-driven chart review, and predictive diagnostics across our entire platform. You'll work alongside world-class researchers and engineers to push the state of the art in applied clinical AI.

Own the training pipeline for our clinical foundation models. You'll work on pretraining, fine-tuning, and evaluation at scale on 4B+ de-identified clinical records.

Responsibilities

• Own the end-to-end training pipeline for our clinical foundation models, from data ingestion to production deployment
• Design and implement pretraining, fine-tuning, and RLHF workflows on 4B+ de-identified clinical records
• Define evaluation frameworks and benchmarks in collaboration with clinical informatics leads
• Drive architectural decisions for next-generation clinical NLP and vision models
• Mentor senior and mid-level engineers; establish ML engineering best practices across the org
• Partner with product and clinical teams to translate research advances into measurable patient outcomes

Requirements

• MS or PhD in Computer Science, Machine Learning, or a related field (or equivalent experience)
• 8+ years of ML engineering experience, including 3+ years at staff/principal level
• Deep expertise in large-scale model training (PyTorch, JAX, or equivalent)
• Proven track record shipping foundation models or large-scale ML systems to production
• Strong understanding of distributed training, mixed-precision, and model parallelism
• Excellent written and verbal communication skills for cross-functional collaboration

Nice to have

• Experience with clinical NLP, EHR data, or HL7/FHIR standards
• Publications at top ML venues (NeurIPS, ICML, ICLR, ACL, EMNLP)
• Experience with HIPAA-compliant data environments
• Background in federated learning or privacy-preserving ML

Compensation: Competitive salary + equity. Details discussed during the process.