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Tasks and Responsibilities:

  • Machine learning model research and development: design, develop and deploy machine learning models for localization and business workflow processes, including machine translation and quality assurance. Utilize appropriate metrics to evaluate model performance and iterate accordingly.
  • Ensure code quality, write robust, well-documented, and structured Python code.
  • Define and design solutions to machine learning problems.
  • Work closely with cross-functional teams to understand business requirements and design solutions that meet those needs.
  • Explain complex technical concepts clearly to non-technical stakeholders.
  • Mentorship: Guide junior team members and contribute to a collaborative team environment.

Success indicators of a Machine Learning R&D Engineer:

  • Effective Model Development: success is evident when the models developed are accurate, efficient, and align with project requirements.
  • Positive Team Collaboration: demonstrated ability to collaborate effectively with various teams and stakeholders, contributing positively to project outcomes.
  • Continuous Learning and Improvement: a commitment to continuous learning and applying new techniques to improve existing models and processes.
  • Clear Communication: ability to articulate findings, challenges, and insights to a range of stakeholders, ensuring understanding and appropriate.

Skills and Knowledge

  • Excellent, in depth understanding of machine learning concepts and methodologies, including supervised and unsupervised learning, deep learning, classification.
  • Hands-on experience with natural language processing (NLP) techniques and tools.
  • Ability to write robust, production-grade code in Python.
  • Excellent communication and documentation skills. Able to explain complex technical concepts to non-technical stakeholders.
  • Experience taking ownership of projects from conception to deployment. Ability to transform business needs to solutions.

Nice to have:

  • Experience using Large Language Models in production.
  • High proficiency with machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn.
  • Hands-on experience with AWS technologies including EC2, S3, and other deployment strategies. Experience with SNS, Sagemaker a plus.
  • Experience with ML management technologies and deployment techniques, such as AWS ML offerings, Docker, GPU deployments, etc.

Education and Experience

  • Master degree in Computer Science, Data Science, Engineering, Mathematics or similar field; PhD is a plus
  • 6+ years of experience in AI/ML research and development.

Job Summary

CompanyWeLocalize
LocationNoida, India
TypeFull-Time
LevelMid-level
DomainSoftware Engineering