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Tier-1 brand plus senior ML role with niche video AI focus yields moderate applicant competition.
Highly specialized ML, computer vision, and cloud platform skills limit cross-industry transferability.
Many mandatory senior-level ML, cloud, infrastructure, and deployment skills enforce strict shortlisting.
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Lead design and development of scalable, cloud-agnostic machine learning platform components for video AI workflows.
Build and maintain APIs, microservices, and AI/ML pipelines covering ingestion to deployment, observability, and continuous improvement.
Drive cloud infrastructure automation and ML model deployment using GCP, Terraform, Kubernetes, and oversee engineering standards and mentorship.
9–12+ years of experience in software engineering for scalable backend and cloud-native systems.
Strong hands-on experience with Google Cloud Platform (GCP), including Vertex AI, GKE, Cloud Run, BigQuery, and related services.
Advanced proficiency in Python, Kubernetes, Terraform, Docker, and infrastructure-as-code practices.
Bachelor’s or Master’s degree in Computer Science, AI, Machine Learning, Engineering or related field (or equivalent experience).
Experienced in architecting and operating large-scale ML platforms with emphasis on video understanding and AI workflows.
Knowledgeable in Deep Learning, Computer Vision, and Generative AI, with practical experience in PyTorch, TensorFlow, and Hugging Face.
Capable of leading cross-team technical strategies, mentoring engineers, and setting standards for reliability, scalability, and maintainability.