Key Responsibilities 1. Data Infrastructure & Pipelines
- Build and maintain data pipelines for collecting, cleaning, and storing data from multiple sources
- Design and manage databases for structured and time-series data
- Create tools for data validation, versioning, and ingestion to ensure model-ready datasets.
- Work closely with the Tech Lead to define API interfaces between the app and AI layer.
2. AI Model Development
Develop and train models for :Scores and recommendationsPredictive analyticsUse both classical ML (regression, clustering) and neural approaches (LSTM, CNNs for time-series).Deploy models via FastAPI / Flask APIs for live inference in the app.3. Analysis & Experimentation
Run experiments to improve model accuracy and personalization.Collaborate with physiotherapists and sports scientists to interpret results and validate model logic.Create dashboards to visualize performance metrics and prediction accuracy.Iterate based on pilot feedback from real users and physio sessions.4. Deployment & Scaling
Manage ML pipeline automation for retraining and continuous improvement.Ensure scalable, low-latency inference for user-facing features.Handle cloud storage and model versioning on AWS / GCP .Ideal Background & Skills
Technical Stack :
Languages : Python (pandas, NumPy, scikit-learn, PyTorch / TensorFlow)Data : PostgreSQL / MongoDB / AWS S3 / BigQueryAPIs : FastAPI, FlaskCloud : AWS / GCP (SageMaker, Lambda, EC2, Cloud Functions)Pipelines : Airflow / Prefect / custom ETL scriptsVisualization : Matplotlib, Plotly, or StreamlitNice-to-Have :
Familiarity with wearable and sensor data (accelerometer, HRV, GPS, power, etc.)Experience with time-series analysis, biomechanics, or exercise physiologyKnowledge of recommendation systems or predictive analyticsExperience with model deployment and MLOpsSoft Skills :
Passion for fitness, health, or sports performanceStrong communication — able to translate data science into plain English for non-technical teammatesComfortable with rapid prototyping and working in ambiguous early-stage environmentsWhat You’ll Get
Ownership of the entire AI backbone of a next-generation fitness platform.Freedom to experiment, deploy, and iterate models that directly impact users’ health outcomes.Work in close collaboration with experts in health tech.Competitive pay + early-stage equity options .