SandboxAQ

Machine Learning Engineer

• 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

Staff Machine Learning Engineer, AI Generation Engine

• 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.
• Contribute to the efforts 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.

Senior Machine Learning Engineer – AI Generation Engine

Product Manager

• Own the product strategy and execution for Finance & Risk Modeling
• Lead rapid prototyping and innovation across a broad range of new ideas
• Operate in a highly ambiguous, fast-changing environment
• Identify, evaluate, and prioritize new AI / LQM use cases
• Serve as a trusted product partner to senior stakeholders

Director of Product Management, AI Generation Engine

Full-stack Engineer

• Own the Platform Architecture: Serve as the final technical authority for the end-to-end software stack, spanning embedded firmware, in-field Linux devices, cloud data pipelines (AWS/GCP), and the clinician-facing web application.
• Product-Ready Foundation: Design clear and flexible interfaces such that our platform can evolve with our product roadmap without major refactors.
• Data Path Integrity: Design and maintain a HIPAA-compliant, production-grade data platform that ensures data confidentiality, integrity, and availability from the sensor to the cloud.
• Hands-on Engineering: This is a player-coach role. You will write code, review complex PRs, debug hardware-software integration issues in the lab, and configure CI/CD pipelines. You lead by doing, setting the standard for code quality and testing. You know what “good” looks like.
• Technical Mentorship: Mentor a growing team of senior and staff engineers, fostering a culture of technical excellence, rigorous review, and psychological safety.
• Drive Quality & Compliance: Lead the engineering team’s adherence to applicable medical device standards (e.g. IEC 62304, ISO 14971) and regulations. You are the gatekeeper ensuring that design outputs (code) meet design inputs (requirements) and that our "move fast" culture never compromises patient safety and critical product functions. Scale strong engineering practices across the team, including design reviews, code review quality, test strategy and technical documentation.
• Cross-functional execution: Partner with Product, Clinical and Regulatory stakeholders to translate product requirements, clinical performance goals and regulatory inputs into concrete, actionable technical plans, engineering specifications and development timelines. Ensure that our software architecture, implementation and documentation support our clinical study needs and regulatory plans (e.g. 510(k) and De Novo).

SandboxAQ

Staff Machine Learning Engineer, AI Generation Engine

Senior Machine Learning Engineer – AI Generation Engine

Director of Product Management, AI Generation Engine

Principal Software Engineer, Medical Devices

Senior Machine Learning Engineer, AI Generation Engine