Principal MLOps / DataOps Engineer – Surgical Robotics AI Platform
About The Position
Horizon Surgical Systems Inc. is revolutionizing the world of surgical ophthalmology by developing a novel, AI driven, and imaging-guided surgical robotic system. Horizon Surgical Systems Inc. aims to expand access to care, provide superior capabilities to the human surgeon, and enhance patient outcomes. Microsurgery in general and Ophthalmology are subfields of surgery for which the surgical outcomes can be significantly improved by robotic systems to allow superior dexterity, precision, accuracy, and visualization beyond the human surgeon’s own capabilities. We are seeking highly motivated, and intellectually inquisitive individuals looking to make a positive impact on healthcare via the development of robotic technology. The core values of Horizon Surgical Systems Inc. are: Commitment to Excellence: We aim to deliver superior patient outcomes and surgeon experiences Passion for Creativity and Innovation: We are driven by new ideas and aim to push the boundaries of what's possible Teamwork and Camaraderie: We achieve our best when we collaborate and work together Welcoming of Critical Opinion: We are enriched by constructive criticism and support the best ideas Personal Accountability: We honor our commitments and take responsibility for our actions You will own the end-to-end data pipeline for a surgical robotics platform operating in live clinical environments. This includes ingesting data from field-deployed medical devices, managing scalable data infrastructure, and ensuring high-quality datasets for training and validating machine learning models. The role spans data engineering and MLOps in an environment with quality/regulatory compliance constraints. The system must handle continuous inflow of multimodal surgical data (imaging, device telemetry), transform it into structured datasets, and support reliable model development under medical device constraints. This is an exciting opportunity to join a high-tech startup that is poised to revolutionize surgical robotics in ophthalmology.
Requirements
- 5–10+ years of experience in data engineering, MLOps, or DataOps roles
- Strong experience building production-grade data pipelines at scale
- Proficiency in Python and SQL
- Experience with workflow orchestration tools (e.g., Dagster, Airflow, Prefect)
- Hands-on experience with AWS (S3, EC2, Lambda, Batch, IAM, etc.)
- Experience designing data lakes or lakehouse architectures
- Familiarity with dataset versioning and experiment tracking tools
- Experience handling large-scale unstructured data (video, images, sensor data)
- Strong understanding of data quality, validation, and observability
Nice To Haves
- Experience in medical devices, healthcare, or other regulated environments
- Familiarity with FDA expectations for data traceability and validation
- Exposure to model monitoring and drift detection frameworks
- Experience working closely with ML researchers and robotics teams
Responsibilities
- Architect and maintain pipelines from device data capture → cloud ingestion → storage → downstream consumption
- Ensure data integrity, traceability, and auditability across the pipeline
- Build scalable ETL workflows for large multimodal datasets
- Implement dataset lineage and reproducibility standards
- Design workflows to for data curation and label QA
- Integrate pipelines with training workflows and experiment tracking
- Support CI/CD for data and model pipelines
- Own cloud-based data architecture (storage, compute, orchestration)
Benefits
- Competitive compensation and an excellent company-paid benefits package.
- performance-based annual bonus
- equity (stock options)
- a comprehensive benefits package
- a generous PTO policy
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What This Job Offers
Job Type
Full-time
Career Level
Principal
Education Level
No Education Listed
