Job Title

Role OverviewWe are seeking Data Scientists with strong foundations in signal processing, sensor fusion, and machine learning for hardware-integrated environments. The role involves close collaboration with quantum sensing, drone engineering, and embedded systems teams to analyze and model multi-sensor datasets including magnetometer, IMU, and UAV telemetry data.The objective is to develop robust navigation, localization, and anomaly detection systems capable of operating in GPS-denied environments through advanced sensor fusion and physics-informed AI models.Key Responsibilities :Sensor Intelligence & Data FusionDesign scalable data ingestion, preprocessing, and cleaning pipelines for magnetometer, IMU, and UAV telemetry streams.Develop physics-informed machine learning models for trajectory estimation, drift correction, and anomaly detection.Implement sensor fusion algorithms including Kalman Filters, Particle Filters, and deep learning architectures (LSTM, Transformer, Graph-based models).Integrate magnetic, inertial, and positional data to enable robust localization in GPS-denied environments.Apply signal processing techniques to extract meaningful patterns from noisy sensor data.Analytics & VisualizationGenerate magnetic anomaly maps and geospatial heatmaps from airborne and terrestrial survey datasets.Perform statistical analysis, clustering, and signal denoising to identify spatial and temporal patterns.Build internal visualization tools and dashboards for real-time monitoring, data interpretation, and mission replay.Collaboration & DeploymentWork closely with hardware and firmware engineers to define data interfaces and synchronization standards for live acquisition.Participate in field testing, calibration campaigns, and post-mission validation of collected sensor data.Document algorithms, experimental results, and contribute to technical proposals, research publications, and intellectual property filings.Ideal Candidate ProfileB.Tech / M.Tech / Ph.D. in Data Science, Physics, Electrical Engineering, Computer Engineering, Robotics, or Applied Mathematics.2–8 years of experience in multi-sensor data analytics, robotics, autonomous systems, or scientific machine learning.Strong programming skills in Python, including experience with NumPy, Pandas, PyTorch/TensorFlow, and Scikit-learn.Solid understanding of signal processing techniques (Fourier transforms, wavelet analysis, filtering, and noise modeling).Experience working with time-series data and probabilistic modeling.Familiarity with Kalman filtering, Bayesian estimation, and sensor fusion algorithms.Experience with geospatial data tools such as GeoPandas, QGIS, or rasterio.Experience working with UAV telemetry, inertial navigation data, or magnetic field mapping is highly desirable.Preferred QualificationsExperience deploying edge AI models using tools such as TensorRT, ONNX, or NVIDIA Jetson platforms.Exposure to defense, aerospace, or geophysical sensing datasets.Familiarity with robotics frameworks such as ROS or simulation environments like Gazebo.Understanding of drone dynamics, navigation systems, and embedded ML inference pipelines.What We OfferOpportunity to work on next-generation sensing and navigation technologies combining AI and advanced hardware systems.Collaboration with a multidisciplinary R&D team including physicists, engineers, and AI researchers.Access to high-fidelity sensor datasets and advanced hardware platforms.Competitive compensation, performance incentives, and opportunities for intellectual property participation.