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Niche agentic AI plus mid-level ML role reduces applicants despite general ML demand.
ML platforms and agentic AI skills transfer across industries but require specialized expertise.
Explicit 5+ years and many mandatory ML, MLOps, cloud, and RL skills enforce strict filtering.
Design, develop, and maintain scalable AI platforms covering data ingestion, processing, model training, and deployment.
Architect and implement agentic AI systems enabling autonomous decision-making and learning in dynamic environments.
Integrate AI/ML models into applications with high performance; implement MLOps practices and ensure security and ethical AI throughout development.
Bachelor's or Master's degree in Computer Science, AI, Machine Learning, or related quantitative field.
5+ years of experience designing, developing, and deploying AI platforms and intelligent systems.
Proficiency in Python, Java, or Go and experience with cloud AI/ML services (AWS, Azure, GCP).
Knowledge of ML algorithms, deep learning frameworks (TensorFlow, PyTorch), containerization (Docker, Kubernetes), and MLOps tools.
Experienced in agentic AI technologies including agent-based modeling, reinforcement learning, or multi-agent systems.
Skilled in architecting cloud-based scalable AI platforms with microservices architecture.
Able to translate business requirements into technical AI solutions and mentor junior engineers.