Principal Machine Learning Engineer
Build and optimize AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists to implement scalable AI solutions on cloud infrastructure.
Build and maintain core GenAI infrastructure including model gateways, vector databases, observability tools, and integration with agent workflows. Requires extensive AI platform experience, Kubernetes, OpenTelemetry/MLFlow, and preferred LLM serving frameworks.
Build and optimize AI/ML pipelines for data processing, model training, and deployment. Collaborate with data scientists to implement scalable AI solutions on cloud infrastructure.
Lead development of computational infrastructure for large-scale neuroscience research, building real-time stimulus/acquisition systems, high-throughput data pipelines, and cloud tools. Requires exceptional full-stack engineering with real-time systems experience; neuroscience background not required.
Lead development of deep learning models for medical image analysis (MRI, X-ray) to accelerate clinical trials, create AI biomarkers, and integrate imaging AI into drug development workflows. Requires PhD and 5+ years building production-grade medical imaging AI.
Principal ML Platform Engineer builds production ML infrastructure for shipping logistics ML (prediction, fraud, optimization). Requires 15+ years engineering, 4+ years ML production systems, Kubernetes/MLflow expertise.
Leads engineering initiatives to build scalable ML platform infrastructure, including unified embeddings, feature pipelines, and continuous learning systems. Requires 7+ years in applied ML, Python/ML frameworks expertise, and Master's/PhD in quantitative field.