Data & AI Engineer

7 days ago

Bengaluru, Karnataka, India TrainTrack Full time ₹ 6,00,000 - ₹ 18,00,000 per year

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 recommendations
  • Predictive analytics
  • Use 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 / BigQuery
  • APIs:
     FastAPI, Flask
  • Cloud:
     AWS / GCP (SageMaker, Lambda, EC2, Cloud Functions)
  • Pipelines:
     Airflow / Prefect / custom ETL scripts
  • Visualization:
     Matplotlib, Plotly, or Streamlit

Nice-to-Have:

  • Familiarity with 
    wearable and sensor data
     (accelerometer, HRV, GPS, power, etc.)
  • Experience with 
    time-series analysis, biomechanics, or exercise physiology
  • Knowledge of 
    recommendation systems
     or 
    predictive analytics
  • Experience with 
    model deployment and MLOps

Soft Skills:

  • Passion for 
    fitness, health, or sports performance
  • Strong communication — able to translate data science into plain English for non-technical teammates
  • Comfortable with rapid prototyping and working in ambiguous early-stage environments

What 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
    .

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