Experience : 3+ years

About the Role :

We're looking for a hands-on ML engineer to build and ship models across Hoomanely's sensor-driven product ecosystem, working closely with the ML Lead on digital signal processing, computer vision, and time series problems. You're comfortable taking a model from an early prototype through to a reliable, production-deployed system.

What You'll Do :

- Build and iterate on ML models for time series, audio signal, and sensor fusion problems, under the guidance of the ML Lead

- Build and maintain data preprocessing and feature engineering pipelines that prepare sensor data for training and inference at scale

- Package and deploy models into production, including on edge or embedded compute, with attention to latency and resource constraints

- Run structured experiments to evaluate model accuracy, generalization, and failure modes, and document findings clearly

- Support monitoring and retraining pipelines that track model performance and drift after deployment

- Work closely with firmware, hardware, and app teams to turn model outputs into clear, actionable product insight

You Might Be a Fit If :

- You have a B.Tech in Computer Science, Electrical Engineering, or related field from a Tier 1 institute (IIT, NIT, BITS Pilani, or equivalent) - mandatory

- You have 3+ years of applied machine learning experience

- You have a solid understanding of time series analysis and at least one of CNNs, RNNs, or signal processing techniques

- You're proficient in Python and at least one ML framework (TensorFlow or PyTorch)

- You've taken at least one model from prototype to a production or near-production deployment

- Bonus : experience with audio signal processing or accelerometer-based activity classification

- Bonus : familiarity with edge deployment of ML models on embedded compute

- Bonus : exposure to MLOps tools and practices

- Bonus : prior experience in IoT, wearables, or health-tech