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Mid-level ML role in a metro with broad skills and known employer increases competition.
Core ML, MLOps, and cloud skills are highly transferable across industries.
Explicit three-year requirement plus mandatory ML, cloud, containerization, and MLOps skills increases filter strictness.
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Design, develop, test, and deploy AI/ML and Generative AI applications including LLM-based solutions, AI assistants, and workflow automation.
Develop APIs and backend services in Python, and deploy AI solutions using Azure, AWS, or GCP cloud platforms.
Build and maintain data pipelines, containerized applications, monitor AI model performance, and collaborate with engineering, product, and data teams to deliver AI solutions.
Bachelor's degree or equivalent (University degree) is mandatory.
Minimum 3 years of relevant work experience in AI/ML software development or data analytics.
Proficiency in Python programming and experience deploying AI applications on cloud platforms like Azure, AWS, or GCP.
Experience with container technologies such as Docker and Kubernetes.
Experienced in designing and validating AI/ML experiments and developing models from hypothesis to deployment.
Capable of integrating AI applications with enterprise platforms and maintaining production AI systems.
Comfortable collaborating across engineering, product, and data teams in an Agile environment and staying current with emerging AI technologies.