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High due to PwC brand, popular AI Engineer title, and broad ML/LLM skill requirements.
Low because ML/AI engineering skills are highly transferable across industries and use cases.
Medium because explicit minimum experience and required ML tooling (Python, TensorFlow, NLP) create moderate filters.
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Design and implement AI systems and scalable machine learning models to transform raw data into actionable insights.
Build and maintain data pipelines and infrastructure to support AI model deployment and reliable AI operations.
Collaborate with stakeholders and team members to enhance AI solutions, drive business growth, and engage in continuous learning to adapt to new AI technologies.
Bachelor’s degree in Engineering or related field, or equivalent specialized training with progressively responsible AI and Machine Learning experience.
At least 1 year of relevant work experience in AI and Machine Learning engineering.
Proficiency in Python and TensorFlow, with experience in machine learning libraries and natural language processing tools like NLTK.
Ability to travel up to 20%.
Possesses academic or professional background in Computer and Information Science, Computer Engineering, or related IT fields.
Holds certifications in data engineering, machine learning, and cloud platforms such as AWS, Google Cloud, Azure, or equivalent.
Experienced in advanced AI techniques including generative AI, AI agent workflows, neural networks, model optimization, and development of scalable, context-aware AI solutions.