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Strong PwC brand, mid-level ML/Ops devops role, metro location, and broad skill requirements increase competition.
Requires ML-Ops and cloud-specific skills, moderately transferable across industries.
Explicit 4+ years plus mandatory ML-Ops, CI/CD, Docker/Kubernetes and cloud networking skills.
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Develop and implement AI-driven data science workflows, machine learning, and deep learning models to enhance automation solutions.
Build and maintain data pipelines, lakes, and optimize data quality and integrity using programming languages like C++, R, and MATLAB.
Collaborate within cloud engineering and data analytics teams to integrate AI and NLP into client solutions, mentor juniors, and uphold professional standards.
Bachelor's degree required.
Minimum 4 years of work experience in relevant fields.
Proficiency in English (oral and written).
Experience with programming (Python and/or Bash), CI/CD pipelines (GitHub Actions or Azure DevOps), containerization (Docker, Kubernetes), and cloud networking concepts.
Educational background preferably in AI, Robotics, Business Analytics, Computer Science/Engineering, Data Science, Machine Learning, Mathematics, Statistics, or related fields.
Experienced in operationalizing ML/LLM systems in production environments with strong programming and cloud infrastructure skills.
Capable of cross-functional collaboration, mentoring team members, and applying analytical thinking to complex problems within AI-driven automation contexts.