Artificial Intelligence and cloud Mlops engineer

Job Title: Senior AI/ML/DL & Cloud Engineer (MLOps | Backend | FastAPI)

Location: Gurugram (Work from Office Only)
Experience: 5+ Years
Department: AI/ML Engineering
Type: Full-time | On-site

About the Role:

We are looking for a Senior AI/ML/DL Cloud Engineer with strong expertise in MLOps, Cloud (AWS/Azure), Kubernetes, CI/CD, and backend development (FastAPI). The ideal candidate will lead and coordinate with cross-functional teams, deliver time-bound results, and handle the complete lifecycle of AI/ML systems — from model development to scalable deployment in production environments.

Key Responsibilities:

• Design, build, and deploy AI/ML/DL solutions with a focus on scalability, performance, and maintainability.
• Develop and maintain end-to-end MLOps pipelines including data ingestion, model training, deployment, and monitoring.
• Work with AWS/Azure cloud platforms, managing compute resources, storage, and networking for ML workloads.
• Manage Kubernetes and Docker for container orchestration and deployment automation.
• Set up and maintain CI/CD pipelines for ML and backend systems.
• Collaborate with backend teams using FastAPI, Python, Flask, or Django for API and service integration.
• Optimize model performance, latency, and reliability for production-grade applications.
• Ensure strong version control, model tracking, and reproducibility practices.
• Coordinate with the AI/DevOps teams to ensure timely delivery of project milestones.
• Maintain high-quality documentation, versioning, and reproducible workflows.

Required Skills & Experience:

• 5+ years of experience in AI/ML/DL and MLOps engineering.
• Strong proficiency in Python, FastAPI, and backend service design.
• Hands-on experience with AWS (SageMaker, EC2, ECR, S3) or Azure (ML Studio, AKS, DevOps).
• Expertise in Docker, Kubernetes, and containerized deployment of ML models.
• Proven experience implementing CI/CD pipelines using GitHub Actions, Jenkins, or Azure DevOps.
• Familiarity with TensorFlow, PyTorch, Scikit-learn, or similar frameworks.
• Strong understanding of microservices architecture and API integration.
• Ability to lead and coordinate with multiple teams efficiently.
• Excellent problem-solving, debugging, and communication skills.
• Must be time-bound, detail-oriented, and result-driven.

Preferred Qualifications:

• Experience in cloud cost optimization for ML workloads.
• Exposure to data engineering tools (Airflow, Kafka, Spark).
• Knowledge of infrastructure as code (Terraform, Helm).
• Prior experience deploying AI solutions in production environments.

Work Location:

Gurugram Office (On-site only)
Candidates must be willing to work and attend interviews in person from our Gurugram office.

Compensation:

Competitive salary based on experience and skill level.

Job Types: Full-time, Permanent

Pay: ₹9,012.33 - ₹63,624.49 per month

Work Location: In person