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Generalist ML/AI role, mid-level range, metro location, and broad skills increase applicant competition.
Core ML, DL, and deployment skills are broadly transferable across industries, lowering background sensitivity.
Explicit 0–5 years range plus mandatory ML/DL, deployment, and Python/framework requirements imply strict filters.
Build, train, fine-tune, and deploy Machine Learning and Deep Learning models in production.
Perform data cleaning, preprocessing, feature engineering, and monitor model performance with retraining as needed.
Collaborate with cross-functional teams and clients to translate business problems into AI/ML solutions and communicate findings effectively.
Experience Required: Fresher to 5 Years in AI/ML or Data Science roles.
Strong knowledge of Machine Learning concepts and algorithms, with hands-on experience in Deep Learning frameworks like TensorFlow, PyTorch, or Keras.
Proficiency in Python and AI/ML libraries, including deployment skills using Flask/FastAPI, Docker, or cloud platforms (AWS/GCP/Azure).
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, or related field.
Comfortable working end-to-end on real-world AI/ML projects including deployment and performance optimization.
Effective in client-facing roles with good communication and documentation skills to present technical insights to stakeholders.
Experience or exposure to MLOps practices, and familiarity with NLP, Computer Vision, or Generative AI is an advantage but not mandatory.