Neuralgo

goML.io - Machine Learning Engineer - Generative AI

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Job Location

in, India

Job Description

Looking for a culture to thrive & build a rewarding career for yourself, join the core team of young hustlers building the next generation of Machine Learning platform & services. You will develop training and deployment pipelines for machine learning, implement model compression algorithms, and productionize machine learning research solving challenging business problems. We are Hiring Machine Learning Engineers at goML Key Responsibilities : - Design and develop generative AI models using techniques like RAG, transformers, and other relevant approaches. - Fine-tune pre-trained LLMs for specific tasks and domains. - Conduct research on new techniques for improving the performance and capabilities of generative AI models. - Apply software engineering rigor and best practices to machine learning /Generative AI pipelines. - Evaluate and analyse the performance of ML/generative AI models. - Stay up to date on the latest advancements in generative AI research. - Facilitate the development and deployment of proof-of-concept Generative AI : - Bachelor's/Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field. - 3-5 years of experience in generative AI or related fields. - Experience in building data pipelines, deploying ML/GenAI models in production, and monitoring and maintaining their performance. - Strong programming skills in Python. - Familiarity with RAG and other techniques for building generative models. - Extensive experience with Git, Docker and a good understanding of Linux for managing servers. - Experience with cloud-based ecosystems, especially AWS ML/GenAI services. - Exposure to ML/GenAI frameworks and tools. - Excellent communication and collaboration skills. - Ability to work independently and in a team-oriented environment. - Methodical and meticulous towards work and planning. (ref:hirist.tech)

Location: in, IN

Posted Date: 11/24/2024
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Neuralgo

Posted

November 24, 2024
UID: 4937080781

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