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    Senior Machine Learning Engineer - Los Angeles, United States - Stealth AI Startup

    Stealth AI Startup
    Stealth AI Startup Los Angeles, United States

    3 weeks ago

    Default job background
    Description

    Join Our Decentralized AI Revolution:
    Founding Machine Learning Engineer Needed

    Are you passionate about decentralizing artificial intelligence and shaping the future of technology? Do you thrive in fast-paced, early-stage startup environments where your contributions make a significant impact?


    As a Machine Learning Engineer specializing in fine-tuning large language models for decentralized AI applications, you'll play a crucial role in pioneering innovative solutions that empower individuals and organizations to harness the power of AI while preserving data privacy and security.


    Here's what you'll be doing:

    Fine-Tuning for Decentralization:
    Fine-tune and optimize large language models for decentralized environments, ensuring robust performance while maintaining data sovereignty and privacy.


    Blockchain Integration:
    Integrate machine learning models with decentralized platforms, leveraging distributed ledger technology to enable secure and transparent AI transactions.


    Privacy-Preserving Techniques:


    Implement state-of-the-art privacy-preserving techniques such as federated learning, differential privacy, and homomorphic encryption to safeguard sensitive data and promote user trust in decentralized AI systems.


    Prototype Development:


    Design, develop, and iterate on decentralized AI prototypes and proof-of-concept applications, demonstrating the feasibility and scalability of our innovative solutions.


    Research & Innovation:
    Stay at the forefront of decentralized AI research, exploring new algorithms, architectures, and methodologies.


    Requirements:


    Strong background in machine learning, deep learning, and natural language processing, with hands-on experience in fine-tuning large language models such as GPT, BERT, or similar.

    Proficiency in programming languages such as Python and experience with frameworks like TensorFlow, PyTorch, or JAX.
    Bachelor's, Master's, or Ph.
    D. degree in Computer Science, Engineering, or a related field.


    Ideal:


    Familiarity with decentralized technologies such as blockchain, smart contracts, and peer-to-peer networks, with a keen interest in applying them to AI systems.

    Solid understanding of privacy-preserving techniques and their application in decentralized AI, including federated learning, differential privacy, and secure multi-party computation.

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