Principal Engineer

2 weeks ago

Bangalore, India Executive Selection India Full time

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 LLMs

8. Proficient in deploying popular pre-trained model like GPT-4, BERT, and their derivatives

9. Familiarity with the foundational architectures in LLMs such as Transformers, GPT variants, BERT, etc

10. Knowledge of optimization techniques for serving LLMs, including quantization, distillation, and on-the-fly sampling methods

11. Bachelor's Degree in Computer Science, Engineering

12. Exceptional problem-solving abilities

13. Excellent communication skills, both written and verbal

14. Design and implement machine learning algorithms tailored for specific research questions or operational needs, ensuring algorithmic fairness and interpretability when applicable

15. Oversee data acquisition, storage, and distribution for machine learning projects, ensuring data quality and compliance with privacy policies

16. Perform data preprocessing including normalization, transformation, and feature engineering to prepare it for machine learning models

17. 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 products

19. Develop automated tools to monitor and report on model performance, identifying and addressing performance degradation or data anomalies as they arise

20. Update models as needed based on performance metrics or new data

21. Articulate machine learning concepts and the implications of model outcomes to non-technical stakeholders through presentations and written documentation

22. Collaborate cross-functionally with business stakeholders, software developers, and other engineers to integrate machine learning solutions into broader company operations

23. 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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