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Popular ML/AI entry role in a metro with generalist requirements yields moderate applicant density.
Machine learning and GenAI skills are highly transferable across industries, so background sensitivity is low.
Explicit 1+ years, degree, and required MLOps/cloud/tool familiarity imply moderately strict shortlisting.
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Design, develop, and deploy advanced AI/ML and Generative AI solutions to solve complex business problems.
Build scalable machine learning models, pipelines, and workflows to enable data-driven decision-making.
Translate technical findings into actionable insights and collaborate with business teams; mentor junior engineers on AI/ML best practices.
Bachelor’s degree in Computer Science, Data Science, AI, or related field.
1+ years of hands-on experience in AI/ML projects (including internships or academic projects).
Proficiency in Python and familiarity with ML libraries such as scikit-learn, TensorFlow, PyTorch, or Hugging Face.
Experience with MLOps tools (MLflow or Vertex AI), cloud platforms (AWS, Azure, or GCP), and basic deployment workflows.
Experience implementing scalable machine learning pipelines and handling production-level AI deployments.
Ability to perform complex statistical analysis and machine learning model architecture design using Python libraries.
Skilled in translating technical concepts for cross-functional collaboration and mentoring junior team members.