Requirements

10+ years of experience building and operating large-scale production Machine Learning systems.
Proven track record of owning ML platforms or infrastructure used by multiple teams or products.
Strong system design skills, with experience making long-term architectural tradeoffs in complex environments.
Expert-level proficiency in Python and strong experience with additional languages such as Scala, Go, or Rust.
Deep hands-on experience with ML frameworks (PyTorch, TensorFlow, scikit-learn) and model lifecycle management.
Extensive experience with MLOps practices, including experimentation frameworks, CI/CD, model monitoring, and reliability.
Strong background in data-intensive and distributed systems (Spark, object storage, large-scale batch and streaming).
Demonstrated ability to lead through influence, mentor senior engineers, and communicate technical strategy to diverse stakeholders.

What you'll be doing

Set long-term technical direction for Kraken’s AI/ML strategy, influencing multiple teams and initiatives.
Own the architecture and evolution of core AI/ML systems, including training, feature management, serving, experimentation, and monitoring.
Lead cross-team efforts to standardize ML development and operational practices across the company.
Drive the design and delivery of complex, high-impact ML systems for use cases such as fraud, risk, personalization, and recommendations.
Partner with senior engineering, product, and data leaders to identify where ML can unlock step-change improvements in scalability and efficiency.
Balance hands-on technical contributions with architectural leadership and design review responsibilities.
Evaluate emerging ML and GenAI technologies and lead their adoption when they provide durable platform-level value.
Mentor Staff and Senior engineers, shaping technical culture and raising the overall quality of ML engineering at Kraken.