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Mid-level popular AI role with broad LLM, MLOps, and cloud requirements increases applicant competition.
Specialized ML/LLM and MLOps skills are transferable across industries but require domain expertise.
Explicit 6+ years plus mandatory ML/LLM, cloud, and MLOps skills enforce strict shortlisting.
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Own end-to-end lifecycle of AI/ML features from concept to production and maintenance.
Design and implement scalable AI systems with focus on performance, security, and accuracy optimization.
Provide technical leadership and mentorship while collaborating cross-functionally on architectural and product roadmaps.
Bachelor’s degree or equivalent experience in relevant field.
6+ years of software engineering experience with proven machine learning model development and deployment.
Proficiency in Python and ML/DL libraries (TensorFlow, PyTorch), plus experience with cloud AI/ML services (GCP, AWS, Azure).
Experience with full software development lifecycle, CI/CD, MLOps tools, and containerization (Docker, Kubernetes).
Demonstrated ability to translate complex business requirements into practical AI solutions within agile and distributed teams.
Deep expertise in modern AI concepts including LLMs, RAG, and agentic workflows, supported by hands-on generative AI platform experience.
Strong technical leadership skills evidenced by mentoring experience and promoting best engineering practices.