Machine Learning Engineer - Sensor Fusion/Signal Processing

Machine Learning Engineer Experience: 3+ years Full-Time | Bengaluru, Work from Office About the Role: We're looking for a hands-on ML engineer to build and ship models across a 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. Responsibilities: - 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 Requirements: - B.Tech in Computer Science, Electrical Engineering, or related field from a Tier 1 institute (IIT, NIT, BITS Pilani, or equivalent) - mandatory - 3+ years of applied machine learning experience - Solid understanding of time series analysis and at least one of CNNs, RNNs, or signal processing techniques - Proficient in Python and at least one ML framework (TensorFlow or PyTorch) - Experience taking at least one model from prototype to a production or near-production deployment Bonus Points: - Experience with audio signal processing or accelerometer-based activity classification - Familiarity with edge deployment of ML models on embedded compute - Exposure to MLOps tools and practices - Prior experience in IoT, wearables, or health-tech Why Join Us: - Ship models that run on real hardware, on real dogs - not just in a notebook - Learn directly from the ML Lead while owning real pieces of the roadmap - Take ownership early, with a direct line to the people building the rest of the product - Join a small, fast-moving team building a category-defining, sensor-driven product