Job Description

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