[Remote] Staff Machine Learning Engineer, AI Generation Engine

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).ResponsibilitiesDesign, construct, and manage robust data pipelines for the training, validation, and continuous retraining of Large Quantitative Models (LQMs) and agentic frameworksDevelop, implement, and rigorously test novel ML models and algorithms, defining appropriate metrics to ensure model performance aligns with high-level product objectivesLead the effort in cleaning, transforming, and engineering features from complex and large-scale datasets to optimize LQM performance and predictive accuracyConduct deep analysis of model behavior, performance, and failure modes, tuning hyper-parameters and optimizing model architecture for efficiency, speed, and accuracy in a production contextCollaborate closely with AI researchers, product managers, and SWEs to translate high-level business objectives into actionable ML development and deployment roadmapsChampion and enforce exceptional engineering standards for code quality, system efficiency, and security in a prototyping environmentDrive technical execution with high autonomy, making critical design and implementation decisions independentlySkillsBS in Software Engineering, Computer Science, or equivalent field of study8+ years of postgraduate experience in software developmentExperience developing highly-available, performant, scalable ML systems, including large-scale data processing pipelinesStrong 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 deploymentDeep 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 datasetsMS or PhD in Software Engineering, Computer Science or equivalent experienceFinancial simulation or technical experience, risk simulationEquivalent experience includes tech leadership in a complex space, driving technical design and execution cross-collaboratively across multiple teams and organizationsExperience with scalable software development on cloud computing platforms (e.g., GCP, AWS)BenefitsComprehensive medical, dental, and vision coverage for employees and dependents with generous employer premium contributionsRetirement savings with company matchingPaid parental leaveInclusive family-building benefitsFlexible paid time offCompany-wide seasonal breaksSupport for flexible work arrangements that enable sustainable performanceOpportunities for continuous learning and growth through on-the-job development, cross-functional collaboration, and access to internal learning and development programsCompany OverviewSandboxAQ 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 SponsorshipSandboxAQ 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.