Staff Machine Learning Engineer, AI Generation Engine
AI summary of the role
Founding ML engineer on the SAIGE team, owning the end-to-end ML lifecycle for AI-first SaaS products built on Large Quantitative Models and agentic frameworks.
What you’ll do
- Design, construct, and manage robust data pipelines for training, validation, and continuous retraining of LQMs and agentic frameworks.
- Develop, implement, and rigorously test novel ML models and algorithms, defining metrics aligned with product objectives.
- Lead feature engineering and optimization of LQM performance from complex, large-scale datasets.
- Conduct deep analysis of model behavior, tuning hyper-parameters and optimizing architecture for production efficiency and accuracy.
What you’ll bring
- BS in Software Engineering, Computer Science, or equivalent.
- 8+ years of postgraduate experience in software development.
- Experience developing highly-available, performant, scalable ML systems with large-scale data processing pipelines.
- Strong expertise in Python and ML stack (PyTorch, TensorFlow, JAX, NumPy, Pandas).
Technologies
PyTorch · TensorFlow · JAX · NumPy · Pandas · Weights & Biases · MLflow · GCP · AWS
About SandboxAQ
Physics-based AI platform delivering Large Quantitative Models across life sciences, finance, materials discovery, and cybersecurity. Spun from Alphabet in 2022.
Series E
Source and classification
Internal deployment & tooling · Evidence for this classification:
inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The AI Generation Engine (SAIGE) team is responsible for rapidly designing, prototyping, and validating AI-first SaaS products that leverage SandboxAQ’s Large Quantitative Models (LQMs) and emerging agentic frameworks. The team operates at high velocity, bridging cutting-edge AI research and production-grade software to unlock new use cases across the company. 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
More from the job description
About SandboxAQ SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The company’s Large Quantitative Models (LQMs) power advances in life sciences, financial services, navigation, cybersecurity, and other sectors. We are a global team that is tech-focused and includes experts in AI, chemistry, cybersecurity, physics, mathematics, medicine, engineering, and other specialties. The company emerged from Alphabet Inc. as an independent, growth capital-backed company in 2022, funded by leading investors and supported by a braintrust of industry leaders. At SandboxAQ, we’ve cultivated an environment that encourages creativity, collaboration, and impact. By investing deeply in our people, we’re building a thriving, global workforce poised to tackle the world's epic challenges. Join us to advance your career in pursuit of an inspiring mission, in a community of like-minded people who value entrepreneurialism, ownership, and transformative impact. The Opportunity The AI Generation Engine (SAIGE) team is responsible for rapidly designing, prototyping, and validating AI-first SaaS products that leverage SandboxAQ’s Large Quantitative Models (LQMs) and emerging agentic frameworks. The team operates at high velocity, bridging cutting-edge AI research and production-grade software to unlock new use cases across the company. Sa [... source excerpt omitted ...] ) 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): Dat [... source excerpt omitted ...] ngineer 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, products 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. Key Responsibilities Design, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworks. Develop, implement, and rigorously test novel ML mo
Employer postings · Data from · Sources