BS in Software Engineering, Computer Science, or equivalent field of study
5+ years of postgraduate experience in software development
Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines
Strong expertise in Python (including the ML stack: PyTorch, TensorFlow, JAX, NumPy, Pandas)
Long, successful history of driving the full ML lifecycle: from initial data exploration and hypothesis testing to architecture, model training, evaluation, and production deployment
Deep proficiency in MLOps and software best practices, including CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow), automated testing, and version control for both code and datasets
MS or PhD in Software Engineering, Computer Science or equivalent experience
Financial simulation or technical experience, risk simulation
Equivalent experience includes tech leadership in a complex space, driving technical design and execution cross-collaboratively across multiple teams and organizations
Experience with scalable software development on cloud computing platforms (e.g., GCP, AWS)