Staff Machine Learning Engineer

Qualifications

• Experience: 8+ years of software or machine learning engineering experience, including 5+ years building, deploying, and operating ML systems in production. Prior experience as a technical lead or the most senior ML engineer on a team.
• Track Record: Demonstrated ownership of ML systems with direct, measurable business impact at scale. Experience in consumer lending, credit underwriting, fraud, or payments strongly preferred.
• Technical Depth:
• Expert-level Python; strong general software engineering fundamentals and system design skills.
• Deep experience with the full ML lifecycle in production: feature engineering, training, evaluation, serving (batch and real-time), monitoring, and retraining.
• Hands-on experience designing ML platform components such as feature stores, model registries, and evaluation frameworks, and making pragmatic build-vs-buy decisions.
• Strong command of gradient-boosted trees and classical ML for tabular data; working knowledge of deep learning frameworks (e.g., PyTorch) where applicable.
• Production experience with cloud infrastructure (AWS or GCP), containerization (Docker, Kubernetes), and modern MLOps and CI/CD tooling.
• Experience working alongside Ruby/Rails backends is a plus.
• Model Risk Fluency: Understanding of model governance in a regulated financial environment, including fair lending considerations, explainability, and model validation practices. Experience working with Risk or Compliance partners on model approval processes is a plus.
• Analytical Rigor: Exceptional ability to frame ambiguous problems, design sound experiments, and reason carefully about causality, selection bias, and the gap between offline metrics and real-world outcomes.
• Leadership and Communication: A history of influencing technical direction beyond your immediate team without formal authority. Able to explain complex modeling decisions and their business implications crisply to executives, and to mentor engineers at all levels.
• Educational Background: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. Advanced degree preferred.
• Equal Employment Opportunity Statement
• Kikoff Inc. is an equal opportunity employer. We are committed to complying with all federal, state, and local laws providing equal employment opportunities and considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
• Please reference the following for more information .