Zooly Labs is an early-stage company on a mission to make advanced surgical guidance more accessible for joint replacement surgery. We build AI-guided technology that combines intelligent sensing, real-time data, and decision support with familiar surgical workflows and standard instruments, without large capital equipment. Our platform spans hip, knee, and shoulder products.
Responsibilities
- Build data pipelines, cleaning and synchronization tools, feature engineering, model evaluation, algorithm validation, visualization, and reproducible analyses.
- Build reusable platform modules instead of one-off, joint-specific solutions wherever you can.
- Take part in sprint planning, design and code reviews, test planning, and documentation.
- Investigate defects and failures and write up root cause and the fix.
- Keep configuration control, test evidence, and clean engineering records.
- Work closely with the product engineers, the US platform leads, and quality/regulatory contributors.
- Define the ground truth, metrics, and failure modes that keep our algorithm claims defensible.
- Deliver predictably within the shared platform cadence, working as one team with the US.
Requirements
- Applied time-series analysis, signal processing, machine learning, sensor analytics, or biomechanics-data work to real algorithm development.
- Strong in Python with PyTorch, TensorFlow, scikit-learn, Pandas, and SQL.
- Solid foundation in statistics, experimental design, model evaluation, cross-validation, uncertainty, and data visualization.
- Built end-to-end ML workflows: ingestion, cleaning and synchronization, labeling, feature engineering, training, validation, evaluation, versioning, and deployment.
- Ability to define meaningful ground truth and metrics and spot bias, leakage, drift, confounding, and failure modes.
- Ability to explain algorithm behavior, limits, and evidence to engineering, clinical, quality/regulatory, and executive audiences.
Nice to have
- Experience with medical devices, surgical data, biomechanics, wearable sensors, robotics, digital health, or other physiologic sensor time-series.
- Experience with quaternions, rigid-body kinematics, sensor fusion, force/pressure signals, event detection, anomaly detection, or real-time inference.
- Experience deploying algorithms into production software, embedded/edge systems, or clinician-facing applications.
- Familiarity with AI/ML medical-device validation, design controls, software lifecycle documentation, and change management.
- Experience working with clinicians or surgeons to define labels, endpoints, clinically interpretable outputs, and prospective data collection.
- Advanced degree (MS or PhD) in a quantitative field.
Additional details
- Role is based in India and works closely with the US team across overlapping hours.
- In-person team environment.
- Equal opportunity employer.
- Responsibilities will evolve as the company and product portfolio grow.
- Compensation, benefits, and employment details will be discussed directly.
Zobhira
