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Remote-first, popular ML role with mid experience but non-Tier1 brand increases competition.
Core ML skills transferable across industries, but NLP/CV specialization moderately limits portability.
Explicit 2–4 year requirement plus mandatory ML/NLP, deep learning, cloud and MLOps skills.
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Implement, deploy, and optimize ML models and algorithms in production environments to improve accuracy and efficiency.
Write clean, scalable code for ML models and APIs and maintain comprehensive documentation.
Conduct data analysis, experiments, and present findings to stakeholders, applying latest AI/ML research to enhance platform capabilities.
Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or related fields.
2-4 years of experience with Python, training/optimizing ML models, NLP, and deep learning.
Experience with TensorFlow/Keras, PyTorch, cloud platforms (AWS, Azure, or Google Cloud), and computer vision and NLP libraries (e.g., OpenCV, spaCy, Hugging Face).
Strong understanding of machine learning concepts, data preprocessing, model governance, and experience with MLOps and CI/CD tools.
Experience working in AI/ML engineering roles with measurable impact deploying models to production.
Proficiency in both machine learning development and operationalization including model optimization and governance.
Comfortable analyzing data, conducting experiments, and communicating complex AI/ML concepts to diverse stakeholders.