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For Employers

Cloud AI Engineer

Intensity Global Technologies Limited

3 years

10 Lacs

delhi india

Posted:1 week ago| Platform:

Apply

Skills Required

ai technology learning aws azure design ml gcp sagemaker vertex data automate model training testing deployment security compliance scalability engineering python tensorflow pytorch containerization docker certifications governance rest microservices communication collaboration agile

Work Mode

On-site

Job Type

Full Time

Job Description

Job Summary

We are seeking a skilled and forward-thinking

Cloud AI Professional

to join our technology team. The ideal candidate will have expertise in designing, deploying, and managing artificial intelligence and machine learning solutions in cloud environments (AWS, Azure, or Google Cloud). You will work at the intersection of cloud computing and AI, helping to build scalable, secure, and high-performance AI-driven applications and services.

Key Responsibilities

Design, develop, and deploy AI/ML models in cloud environments (AWS, GCP, Azure).
Build and manage end-to-end ML pipelines using cloud-native tools (e.g., SageMaker, Vertex AI, Azure ML).
Collaborate with data scientists, engineers, and stakeholders to define AI use cases and deliver solutions.
Automate model training, testing, and deployment using MLOps practices.
Optimize performance and cost of AI/ML workloads in the cloud.
Ensure security, compliance, and scalability of deployed AI services.
Monitor model performance in production and retrain models as needed.
Stay current with new developments in AI/ML and cloud technologies.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
3+ years of experience in AI/ML and cloud computing.
Hands-on experience with cloud platforms (AWS, GCP, or Azure).
Proficient in Python, TensorFlow, PyTorch, or similar frameworks.
Strong understanding of MLOps tools and CI/CD for machine learning.
Experience with containerization (Docker, Kubernetes).
Familiarity with cloud-native data services (e.g., BigQuery, S3, Cosmos DB).

Preferred Qualifications

Certifications in Cloud (e.g., AWS Certified Machine Learning, Google Cloud Professional ML Engineer).
Experience with generative AI, LLMs, or real-time inferencing.
Knowledge of data governance and ethical AI practices.
Experience with REST APIs and microservices architecture.

Soft Skills

Strong problem-solving and analytical skills.
Excellent communication and collaboration abilities.
Ability to work in a fast-paced, agile environment.

Skills:- Machine Learning (ML), Amazon Web Services (AWS), Python, PyTorch and TensorFlow

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Cloud AI Engineer