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Principal Engineer - Artificial Intelligence/Machine Learning


Executive Selection India


Location

Bangalore | India


Job description

Job Description :1. This role will be Work From Office at Bellandur, Bengaluru.2. A minimum of 8 years of Artificial Intelligence/Machine Learning experience.3. Strong programming skills in Python, C++, or other relevant languages.4. Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.5. Strong knowledge of machine learning algorithms and principles.6. Experience with cloud computing services (AWS, Azure, GCP, etc.)7. Comprehensive understanding of training LLMs8. Proficient in deploying popular pre-trained model like GPT-4, BERT, and their derivatives9. Familiarity with the foundational architectures in LLMs such as Transformers, GPT variants, BERT, etc10. Knowledge of optimization techniques for serving LLMs, including quantization, distillation, and on-the-fly sampling methods11. Bachelor's Degree in Computer Science, Engineering12. Exceptional problem-solving abilities13. Excellent communication skills, both written and verbal14. Design and implement machine learning algorithms tailored for specific research questions or operational needs, ensuring algorithmic fairness and interpretability when applicable15. Oversee data acquisition, storage, and distribution for machine learning projects, ensuring data quality and compliance with privacy policies16. Perform data preprocessing including normalization, transformation, and feature engineering to prepare it for machine learning models17. Develop machine learning models using frameworks like TensorFlow or PyTorch, focusing on scalability and efficiency.18. Translate research algorithms into production-level code that can be integrated into existing platforms or products19. Develop automated tools to monitor and report on model performance, identifying and addressing performance degradation or data anomalies as they arise20. Update models as needed based on performance metrics or new data21. Articulate machine learning concepts and the implications of model outcomes to non-technical stakeholders through presentations and written documentation22. Collaborate cross-functionally with business stakeholders, software developers, and other engineers to integrate machine learning solutions into broader company operations23. Collaborate with DevOps teams to deploy machine learning models in a cloud-based environment, ensuring that models are easily maintainable, scalable, and robust. (ref:hirist.tech)


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