Note The job is a remote job and is open to candidates in USA. SandboxAQ is a high-growth company delivering AI solutions that address some of the world's greatest challenges. The AI Generation Engine (SAIGE) team is seeking a highly accomplished Machine Learning Engineer to take ownership of the end-to-end ML lifecycle, focusing on designing and building AI-first products that leverage Large Quantitative Models (LQMs).

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 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 Skills 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 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

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 Company Overview SandboxAQ develops AI and quantum technology solutions that enhance biopharma, cybersecurity, and materials science. It was founded in 2016, and is headquartered in Palo Alto, California, USA, with a workforce of 51-200 employees. Its website is https//www.sandboxaq.com. Company H1B Sponsorship SandboxAQ has a track record of offering H1B sponsorships, with 7 in 2025, 6 in 2024, 3 in 2023, 5 in 2022, 1 in 2021, 5 in 2020. Please note that this does not guarantee sponsorship for this specific role.