Machine Learning Engineer - Time Series Analysis

Job Title: Machine Learning Engineer - Time Series Analysis Company: Swasti Job Category: Machine Learning Roles & Responsibilities: About The Role We're looking for a hands-on ML engineer to build and ship models across our 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. * 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 * 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 Work Location: Bengaluru, Karnataka, India Availability: Full time

* 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 * Proficiency 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 * 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 Key Skills: Machine Learning, Python, TensorFlow, PyTorch, Feature Engineering, Computer Vision Salary: Not disclosed