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About the role
As an Applied Scientist at Altair, you will be involved in developing advanced technologies for underwater sensing and classification systems using acoustic signal processing and machine learning. Your primary responsibilities will include: - Developing algorithms for acoustic signal detection, feature extraction, spectral analysis, time-frequency analysis, noise suppression, filtering, detection and classification, signature recognition, anomaly detection, multi-sensor data fusion, and acoustic fingerprinting. - Working extensively with hydrophone data, vector sensor data, multi-channel acoustic recordings, and low signal-to-noise ratio environments. - Designing and implementing machine learning systems for acoustic target classification, signature recognition, event detection, anomaly detection, few-shot learning, self-supervised learning, and representation learning. - Studying and implementing state-of-the-art research in signal processing and machine learning, translating research concepts into deployable engineering solutions, designing experiments and evaluation methodologies, and contributing to the long-term technical roadmap of Altair's underwater sensing systems. Qualifications required for this role include: - Education: M.Tech, MS (Research), ME, or PhD in disciplines such as Signal Processing, Electrical Engineering, Electronics & Communication Engineering, Applied Mathematics, Physics, Acoustics, Ocean Engineering, Communication Systems, or Control Systems. - Technical Skills: Strong experience in signal processing, digital signal processing, statistical signal processing, detection & estimation theory, spectral analysis, adaptive filtering, time-frequency analysis, feature extraction, time-series analytics, pattern recognition, machine learning, classification systems, anomaly detection, representation learning, self-supervised learning, probabilistic models, and deep learning for sensor data. Proficiency in Python, NumPy, SciPy, and PyTorch is required. Preferred experience in domains such as acoustics & sonar, underwater acoustics, sonar signal processing, hydrophone data analysis, vector sensor processing, passive acoustic monitoring, signal intelligence & sensing, radar signal processing, RF signal classification, acoustic & acoustic AI, speech processing, and audio scene analysis will be advantageous. Join Altair to work on technically challenging AI and sensing problems in defence, build next-generation underwater awareness and classification systems, collaborate with multidisciplinary teams, and create novel technology with real-world operational impact. This is not a generic AI, LLM, Generative AI, NLP, or Data Science role, so candidates with strong foundations in signal processing, sensing systems, acoustics, applied mathematics, radar, sonar, RF, or related engineering disciplines are preferred. Interested candidates are encouraged to share their CV, publications, patents, GitHub profile, and relevant research work for consideration. As an Applied Scientist at Altair, you will be involved in developing advanced technologies for underwater sensing and classification systems using acoustic signal processing and machine learning. Your primary responsibilities will include: - Developing algorithms for acoustic signal detection, feature extraction, spectral analysis, time-frequency analysis, noise suppression, filtering, detection and classification, signature recognition, anomaly detection, multi-sensor data fusion, and acoustic fingerprinting. - Working extensively with hydrophone data, vector sensor data, multi-channel acoustic recordings, and low signal-to-noise ratio environments. - Designing and implementing machine learning systems for acoustic target classification, signature recognition, event detection, anomaly detection, few-shot learning, self-supervised learning, and representation learning. - Studying and implementing state-of-the-art research in signal processing and machine learning, translating research concepts into deployable engineering solutions, designing experiments and evaluation methodologies, and contributing to the long-term technical roadmap of Altair's underwater sensing systems. Qualifications required for this role include: - Education: M.Tech, MS (Research), ME, or PhD in disciplines such as Signal Processing, Electrical Engineering, Electronics & Communication Engineering, Applied Mathematics, Physics, Acoustics, Ocean Engineering, Communication Systems, or Control Systems. - Technical Skills: Strong experience in signal processing, digital signal processing, statistical signal processing, detection & estimation theory, spectral analysis, adaptive filtering, time-frequency analysis, feature extraction, time-series analytics, pattern recognition, machine learning, classification systems, anomaly detection, representation learning, self-supervised learning, probabilistic models, and deep learning for sensor data. Proficiency in Python, NumPy, SciPy,