Live opening · Posted 11 days ago
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We are seeking a highly skilled AI Engineer with a strong foundation in backend development and cloud technologies, particularly within the Microsoft ecosystem. The ideal candidate will have experience in AI/ML domains such as Gen AI, Natural Language Processing (NLP), LLM, Computer Vision, Video Processing, Text Extraction, Dubbing, Transcription, and Translation, Text to Video Generation, Recommendation System, Automated TV Subtitling and be proficient in building scalable, production-ready systems using modern cloud platforms.
Responsibilities:
Design and develop advanced backend components, data systems, pipelines, and microservices for AI-driven applications.
Engineer and implement production-ready, cloud-native infrastructures (or on-premise), from databases to serverless architectures.
Integrate and deploy AI models and services, including NLP, computer vision, and video processing solutions.
Utilise Azure AI Services, Cognitive Services, and other cloud-native AI tools to build intelligent applications.
Collaborate with cross-functional teams to deliver scalable and maintainable AI solutions.
Follow best practices in software engineering, including CI/CD, testing, and documentation.
Requirements:
Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
AI/ML experience, especially in Gen AI, NLP, LLM, Computer Vision, Video Processing, Text Extraction, Dubbing, Transcription, Translation, Text to Video Generation, Recommendation System, and Automated TV Subtitling, is highly desirable.
Proven experience as a senior software or data engineer, with a strong backend focus.
Advanced proficiency in Python, demonstrated through real-world projects.
Practical experience with backend technologies and frameworks.
SQL, PySpark and Data engineering experience are strong advantages.
Expertise in Microsoft Azure, including Azure AI Services and Cognitive Services.
Familiarity with AWS, AWS AI Services / Google Cloud Platform (GCP).
Strong knowledge of CI/CD frameworks / MLOps, and DevOps practices.
Experience with Docker and Kubernetes for containerization and orchestration.
Experience
4-8 yrs
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