Machine Learning Engineer - Time Series Analysis in Bangalore, भारत

Machine Learning EngineerFull-TimeLocation : Bengaluru, Work from OfficeQualifying Degree : https://jobeax.com/link/2DENLGgQM7whDhaE from a Tier 1 InstituteExperience : 3+ yearsAbout 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 https://jobeax.com/link/fjg1eCkr5EQQjnLW 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 insightYou Might Be a Fit If :- You have a https://jobeax.com/link/2DENLGgQM7whDhaE 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 (ref:hirist.tech)