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Niche GenAI/MLOps skills reduce applicants, but known employer and visible role keep competition medium.
ML/AI and MLOps skills transfer across industries moderately, so background fit sensitivity is medium.
Explicit 7+ years plus mandatory ML/GenAI, cloud, and MLOps skills create strict shortlisting filters.
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Lead development and production deployment of AI/ML solutions from ideation through PoC, pilot, and production stages.
Design and implement cloud-native architectures using microservices, APIs, Docker, Kubernetes, and CI/CD for scalable, cost-optimized AI systems.
Translate complex business problems into scalable technical AI solutions while ensuring observability, deployment strategy, and cloud security compliance.
Bachelor's or Master's degree in Engineering, Computer Science, AI/ML, or related field.
7+ years of experience in product development, R&D, or advanced technology roles.
Technical expertise in cloud platforms (AWS/GCP/Azure), microservices, Docker, Kubernetes, Python, SQL, AI/ML frameworks, GenAI, LLMs, RAG, vector databases, and MLOps.
Experience with 12-factor apps, serverless design, autoscaling, high availability, deployment strategies (blue/green, canary), and cloud security standards.
Proven track record of taking AI/ML concepts from ideation through production at scale in cloud-native environments.
Experienced in mentoring engineers and navigating high-ambiguity, fast-evolving technology projects.
Strong communicator with ability to align technical AI solutions with business needs and operational goals.