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.
About the Role:
AQMed is revolutionizing diagnostics, starting with CardiAQ™, a noninvasive device set to tackle the world's leading cause of death. Cardiovascular disease diagnostics are ripe for disruption, and CardiAQ™ is our answer—a device utilizing sophisticated magnetocardiography (MCG) enhanced by AI to offer faster, more accurate results than ever before.
This groundbreaking innovation hinges on mastering the torrent of complex data it generates. We seek a visionary Staff Data Engineer for Operations to architect and command this critical asset. Your primary directive will be forging the robust, scalable infrastructure needed to transform raw data into revolutionary insights. You will take full ownership of our AWS data backbone, engineering a streamlined, reliable system from a challenging, growing dataset. By empowering our scientific pioneers with pristine data, you will directly accelerate discovery and impact the future of healthcare in our dynamic startup environment. This is your opportunity to build, to own, and to leave your mark.
What You'll Do:
- Design and manage scalable data pipelines on AWS to support AI-driven medical research.
- Oversee core data systems, ensuring high uptime, data quality, and efficient batch workflows.
- Create and refine data ingestion, transformation, and storage processes for research use.
- Automate data processing pipelines to improve reliability, speed, and reproducibility.
- Build and maintain automated ML training and reporting workflows to support model development and monitoring.
- Use AWS services (like S3 and related tools) to build cost-effective, reliable data solutions.
- Develop and enforce consistent data practices, architecture, and documentation.
- Work closely with scientists, ML engineers, and medical experts to meet data needs.
- Build data systems that meet healthcare regulations and prioritize privacy.
Who You Are:
- Bachelor's or Master's Degree in Computer Science, Computer Engineering, Mathematics, Physics, Statistics, or other relevant technical discipline.
- 8+ years of experience as a Data Engineer, focusing on data operations.
- Extensive experience working with large datasets in a cloud environment, specifically AWS.
- Strong proficiency in AWS data tools and services (e.g., S3).
- Experience with data pipeline development and batch processing.
- Experience with programming languages related to data engineering tools and frameworks such as Spark, Scala, Hadoop, Python, or similar.
- Proficiency with SQL and databases
- Comfortable working in a collaborative, fast-paced team with a strong mission.
- Proactive, self-driven, and excited to learn new technologies and approaches.
- Demonstrates strong ownership by proactively taking initiative, accountability, and attention to detail.
Nice to haves:
- Exposure to multichannel sensor data or time series data (e.g., ECG/EKG, medical device data)
- Experience with MLOps and exposure to machine learning workflows
