Senior ML Engineer – MLOps & Mechanistic Interpretability
Core
Build MLOps infrastructure and mechanistic interpretability frameworks for next-generation credit risk engines, mapping latent embeddings to human-readable concepts for regulatory compliance.
Role type
Senior IC ML Engineer (MLOps & Mechanistic Interpretability) with team leadership
Builds
Scalable Transformer-based model deployment pipelines and 'glass box' tooling for credit risk engines
Domain
Financial services / Credit risk / Mechanistic Interpretability (XAI)
Deliverable
production ML models
Required skills
MLOps pipeline design, Transformer model deployment, Mechanistic Interpretability (XAI), latent embedding mapping, regulatory compliance engineering, technical leadership, patent/IP development, system architecture design
Preferred skills
Master's degree in AI/ML, cloud certifications, team management experience
Technologies
Transformer models, MLOps frameworks, credit risk engines
Responsibilities
Design systems for training and running ML models, define projects and scope for engineering teams, develop and report intellectual property, collaborate on product development from analysis to deployment, mentor colleagues and promote best practices
Seniority
Senior, hands-on IC with team leadership
