Note: The job is a remote job and is open to candidates in USA. The client is a hyper-growth startup revolutionizing healthcare AI by building real-world simulation environments for training and evaluating advanced medical AI models. The Machine Learning Engineer will architect and scale backend services, data pipelines, simulation environments, and evaluation infrastructure for complex clinical data and high-volume AI workflows.
Responsibilities
- Architect, build, and scale the high-stakes backend services and massive data pipelines required to process incredibly complex, unstructured clinical data
- Own the end-to-end development of groundbreaking simulation environments where frontier AI models practice real medicine and are evaluated against actual human outcomes
- Drive the core system architecture and technical vision as the platform scales aggressively to meet an explosion of demand from top-tier AI labs
- Collaborate closely with industry-leading AI systems experts to invent and deploy new evaluation frameworks, reward functions, and clinical benchmarks
- Bulletproof the infrastructure, guaranteeing flawless reliability, massive performance, and crystal-clear observability across all data ingestion and evaluation systems
Skills
- 6+ years of heavy-hitting professional software engineering experience, specifically dominating massive backend systems, data engineering, or cutting-edge AI infrastructure
- Battle-tested production experience building relentless, high-volume data pipelines and processing incredibly complex datasets at scale using Python, PostgreSQL, and modern cloud architecture
- A proven track record of designing infinitely scalable architectures to support machine learning, Generative AI workflows, or complex, high-volume data transformations
Benefits
- Equity
Company Overview