Senior ML Engineer

📋 Description

• Lead ML platform engineering initiatives: Design, develop, deploy, and operate complex platform
• Build scalable ML infrastructure: Develop robust solutions for model deployment and serving
• Improve platform reliability and performance: Build reusable components, standards, and automation
• Own technical projects end to end: Translate business requirements into technical designs, evaluate
• Drive production troubleshooting: Lead investigations into complex production incidents, identify
• Collaborate across technical and business teams: Partner with Data Science, Product, Risk, Fraud

🎯 Requirements

• Professional software engineering experience: At least 5 years of experience building, deploying
• Strong software engineering fundamentals: Deep understanding of API design, distributed systems
• Cloud-native and scalable systems: Demonstrated experience designing and operating reliable
• ML platform and MLOps expertise: Practical experience with machine learning platforms, model
• Understanding of the ML lifecycle: Familiarity with the processes involved in feature engineering
• Infrastructure and deployment technologies: Experience with Docker, Kubernetes, CI/CD pipelines

🎁 Benefits

• Additional qualifications that are advantageous: Experience with cloud and data technologies such
• Experience developing feature platforms, model-serving infrastructure, workflow orchestration
• Familiarity with monitoring model quality, data quality, feature coverage, inference latency
• Experience working with sensitive data in regulated industries, particularly financial services.
• Proficiency in Java or another backend programming language in addition to Python.
• Familiarity with AI-powered productivity tools such as ChatGPT or GitHub Copilot.