Staff Machine Learning Engineer, AI Generation Engine

🕒 May 27

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SandboxAQ

51 - 200 employees

Founded 2021

đŸ€– Artificial Intelligence

🔒 Cybersecurity

💊 Pharmaceuticals

Artificial Intelligence ‱ Cybersecurity ‱ Pharmaceuticals

SandboxAQ is a company developing quantitative AI and quantum-inspired technologies to solve real-world problems across drug discovery, materials science, cybersecurity, and navigation. They build large quantitative models (LQMs) grounded in physics and chemistry to predict molecular properties, accelerate therapeutic design, and simulate complex chemical and catalytic processes, while also applying their expertise in AI and post-quantum cryptography to enhance digital security and navigation in GPS-denied environments.

📋 Description

‱ 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 models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectives ‱ Lead the effort in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracy ‱ Conduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production context ‱ Collaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmaps ‱ Champion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environment ‱ Drive technical execution with high autonomy, making critical design and implementation decisions independently

🎯 Requirements

‱ 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 ‱ 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

đŸ–ïž Benefits

‱ Comprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributions ‱ Retirement savings with company matching ‱ Paid parental leave ‱ Inclusive family-building benefits ‱ Flexible paid time off ‱ Company-wide seasonal breaks ‱ Support for flexible work arrangements that enable sustainable performance ‱ Opportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programs

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