Senior Machine Learning Engineer, AI Generation Engine

Role Description

SandboxAQ's AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, from initial data exploration and model development to scalable production deployment. This role is central to designing and rapidly building AI-first products that incorporate Large Quantitative Models (LQMs) and sophisticated agentic frameworks.

We are looking for a hands-on engineer who is passionate about owning the entire lifecycle of model development. This requires significant industry experience in bringing machine learning models from conception and experimentation to production and deployment in a robust, scalable manner, including (but not limited to):

• Data Acquisition and Curation
• Infrastructure
• Pre-Training
• Evaluations
• Fine-Tuning

This person will be one of the founding engineers to join the SAIGE team and will be the bridge between cutting-edge AI concepts and functional, real-world MVPs.

As a Machine Learning Engineer on the SAIGE team, your primary goal will be to rapidly iterate on different potential solutions to build and evaluate new models, focusing on speed and tangible outcomes. You'll be part of a diverse team consisting of software engineers, ML experts, product managers, and user experience researchers, where they will play a key role in efficient and effective enablement of the cutting-edge technologies being developed at SandboxAQ.

Qualifications

• 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.

Requirements

• 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)

Benefits

• Competitive salary, equity, and annual bonus
• 401k matching at 50% up to IRS maximum contribution
• Unlimited PTO plus a summer and winter break (one week each)
• Twelve weeks of fully paid parental leave in the US, with another 8 weeks for birthing parents
• $750 equipment, software, and office furniture budget
• $100 per month for wellness (physical or mental) and $100 for home office bills
• Top-notch medical, dental, and vision insurance for you and your dependents with all premiums covered at 95% for employees
• Family Planning support (fertility, surrogacy, adoption) through Carrot