SandboxAQ
AI Solutions
StaffMachineLearningEngineer,AIGenerationEngine
Neural analysis suggests this role is
optimal for Staff candidates.
“Staff Machine Learning Engineer, AI Generation Engine at SandboxAQ. Skills: Machine Learning, ML Lifecycle, Production Deployment, Python. Design data pipelines. Develop ML models”
What You'll Achieve.
Rapidly building AI-first products; Unlock new use cases; Optimize LQM performance; Achieve high-level product objectives; Tangible outcomes
Industry & Context.
Problem-solving
What They're Looking For.
Must Have
BS in Software Engineering, Computer Science, or equivalent field of study, 8+ years of postgraduate experience in software development, Experience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelines, 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
Nice to Have
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)
What You'll Do.
Design data pipelines
Analyze model behavior
Collaborate with researchers
Champion engineering standards
Drive technical execution
How You'll Work.
Team & Collaboration
Collaborate closely with AI researchers, product managers, and SWEs; Cross-collaboratively across multiple teams and organizations
Full 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. 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 conce
Applying for this Staff Machine Learning Engineer, AI Generation Engine role?
Most applicants get filtered before a human reads their resume. See if yours makes the cut.
How to Apply on Ashby
- Ashby is a fast modern ATS — most applications take under 3 minutes.
- The resume parser is strong; verify parsed experience dates and job titles.
- Custom screening questions are often scored algorithmically — answer completely.
- Location field affects geo-based screening; use your actual metro area.
ANONYMOUS · UNFILTERED
What do employees actually say about SandboxAQ?
Real rants from real employees. Read before you apply.