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    Home/Jobs/AI/ML Engineer: SIGINT

    AI/ML Engineer: SIGINT

    Auric AI

    Mumbai / Bengalore
    3-5 years
    Today
    ₹10–20 LPA
    Full-time
    Onsite

    Skills Required

    Machine Learning
    Deep Learning
    Python
    TensorFlow
    PyTorch
    Signal Processing
    Radar
    Communications

    Description

    Auric AI Labs is developing an AI-powered vision intelligence platform for defense applications. The company is looking for an AI/ML Engineer to build deep learning models for detecting, classifying, geolocating, and fingerprinting radar and communications emitters from raw IQ data.

    Company: Auric AI

    Role: AI/ML Engineer: SIGINT & ELINT

    Location: Bengaluru/Mumbai (Onsite)

    Key Skills:

    • AI-native architecture
    • deep learning
    • raw IQ data
    • signal processing
    • ML
    • Python
    • simulated data pipeline

    Role Focus:

    • Design and build deep learning models to detect, classify, geolocate, and fingerprint radar and communications emitters directly from raw IQ data
    • Develop a synthetic data pipeline, channel models, and validation methodology
    • Design experiments to test and validate the models
    • Translate vague objectives into defensible ML problems

    Nice to have:

    • Experience with complex-valued signals, long-range temporal dependencies, and small distribution shifts
    • Knowledge of DSP principles and limitations

    Other:

    • The model is the product, not an 'AI feature' inside a conventional product
    • The company is betting on an AI-native architecture to deliver a 5-10x improvement on various metrics

    Prepare for this role

    Recommended resources to build the skills for this position. Sponsored.

    Python for Everybody Specialization

    Coursera

    Learn Python from scratch — variables, data structures, web scraping, and databases.

    Python 3 Programming Specialization

    Coursera

    Intermediate Python covering classes, inheritance, APIs, and data processing.

    Deep Learning Specialization

    Coursera

    Five-course deep learning series covering CNNs, RNNs, transformers, and ML strategy.

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