Sr./Staff Machine Learning Engineer

Responsibilities

• Scale and optimize existing ML systems, including feature stores, model serving, and orchestration pipelines.
• Build reproducible, automated ML pipelines for model training, deployment, and monitoring.
• Partner with data scientists to enable low-latency production deployment.
• Design and implement new components of the ML stack for scalability, modularity, and developer experience.
• Set ML engineering standards, best practices for model deployment, monitoring, and lifecycle management; mentor teammates.
• Own production reliability for ML systems serving real-time decisions.

Requirements

Required:

• 4+ years building and maintaining production ML infrastructure.
• Strong software engineering fundamentals; experience designing distributed systems and writing high-quality code.
• Hands-on with full ML lifecycle: feature engineering/serving, model deployment, monitoring, retraining.
• Proficiency in Scala and Python; experience with Spark and Flink.
• Experience operating systems at scale: performance tuning, observability, incident response.
• Strong communication and collaboration skills.
• Significant experience with AWS.

Strongly Preferred:

• Building ML infrastructure for fintech applications.
• Scaling ML systems through growth in traffic, models, or features.

Nice to Have:

• Prior ML engineer experience at a startup.

Compensation & Benefits

• Competitive salary and equity packages, including 401k.
• 100% employer-covered health, dental, vision insurance.
• Unlimited PTO.
• Remote-first culture.