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Mid-level experience, metro location, and broad ML skillset increase applicant competition.
Requires ML-specific skills and deployment experience, moderately limiting cross-industry transferability.
Explicit 4–6 years, specific ML tech stack, deployment and leadership requirements make shortlisting strict.
Lead and mentor a team of AI/ML engineers and data scientists to deliver machine learning solutions.
Design, deploy, and scale production-grade machine learning models across various domains.
Collaborate with cross-functional teams to translate business requirements into AI/ML applications and drive experimentation and innovation.
4 to 6 years of experience in machine learning and AI application development.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or related field.
Proficiency in Python and ML libraries (TensorFlow, PyTorch, scikit-learn).
Experience deploying ML models on cloud platforms such as AWS, GCP, or Azure.
Experienced in team leadership with mentoring and communication skills in AI/ML contexts.
Strong technical background in supervised/unsupervised learning, NLP, and computer vision.
Operational mindset toward production deployment, scalability, and cross-functional collaboration.