Senior Machine Learning Engineer (AI Generation Engine)

Role overview

Join SandboxAQ’s SAIGE (AI Generation Engine) team as a Senior Machine Learning Engineer. You’ll be a founding engineer, owning the end-to-end ML lifecycle—from data exploration and model development through scalable production deployment—while rapidly iterating on solutions to build and evaluate new models.

Responsibilities

• Own the full ML lifecycle: data exploration, hypothesis testing, model development, and production deployment.
• Design, build, and manage robust data pipelines for training, validation, and continuous re-training.
• Develop, implement, and rigorously test new ML models and algorithms; define appropriate evaluation metrics.
• Collaborate with AI researchers, product managers, and software engineers to translate business objectives into ML development and deployment roadmaps.

Requirements

• Hands-on engineer passionate about owning model development to production.
• Strong experience bringing ML from conception/experimentation to robust, scalable deployment across the lifecycle (e.g., data acquisition/curation, infrastructure, pre-training, evaluation, fine-tuning).
• 5+ years of postgraduate experience in software development.
• Strong expertise in Python and ML stack including PyTorch, TensorFlow, JAX, NumPy, Pandas.
• Deep proficiency in MLOps and software best practices:
  • CI/CD for ML, experiment tracking (e.g., Weights & Biases, MLflow)
  • Automated testing and version control for both code and datasets
• Experience building highly available, performant, scalable ML systems.
• Experience with large-scale data processing pipelines.
• Cloud experience on GCP and/or AWS.
• BS in Software Engineering, Computer Science, or equivalent (MS/PhD preferred).

Nice to have

• Technical leadership experience in cross-collaborative, multi-team environments.
• Financial simulation or risk simulation experience.