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Metro location plus visible senior ML role yields moderate applicant competition.
Core ML modeling and production pipeline skills are broadly transferable across industries.
Explicit 9–12 years requirement and mandatory ML frameworks, deployment, and cloud experience increase screening strictness.
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Design, build, and scale end-to-end production-grade AI and machine learning systems that deliver measurable business impact.
Lead AI solution development from problem definition through deployment, adoption, and continuous improvement, partnering with Product, Engineering, and Delivery teams.
Provide technical guidance and mentoring to junior engineers, ensuring quality and performance of AI systems.
Bachelor’s degree in related field.
9–12 years of relevant experience in machine learning model development and deployment.
Proficiency in programming languages such as Python, R, or Java, and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
Experience with cloud platforms and scalable computing resources.
Experienced in leading AI system design and operationalization across cross-functional teams in production environments.
Strong foundation in statistics, optimization, probability theory, and experimental methodologies relevant to machine learning.
Comfortable working in hybrid work environments requiring strong communication and collaboration skills.