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Medium — metro location, sought-after ML role and broad skillset attract applicants, senior requirement mitigates density.
Medium — core ML engineering skills transfer across industries, but Azure and specialized video/NLP domain increase specificity.
Medium — multiple mandatory technical skills and senior experience expected, but no explicit years filter.
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Design and develop backend components, data systems, pipelines, and microservices for AI-driven applications.
Engineer and implement production-ready cloud-native or on-premise infrastructures including databases and serverless architectures.
Integrate and deploy AI models and services leveraging Azure AI Services, Cognitive Services, and cloud-native AI tools, covering NLP, computer vision, and video processing.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
Proven experience as a senior software or data engineer with a strong backend focus.
Advanced proficiency in Python and practical experience with backend technologies; SQL, PySpark, and data engineering experience preferred.
Experience with Microsoft Azure (including Azure AI and Cognitive Services); familiarity with AWS or GCP AI services also required.
Immediate joiner status required.
Expertise in AI/ML domains such as Gen AI, NLP, LLM, computer vision, video processing, text extraction, dubbing, transcription, translation, or related AI-driven media technologies.
Strong operational background in cloud-native AI infrastructure and MLOps/DevOps practices including CI/CD, containerization with Docker, and orchestration with Kubernetes.
Experience working in cross-functional teams to deliver scalable and maintainable AI solutions with an emphasis on backend engineering and data systems.