Urgent opening for Ai/ML Engineer
Job Title: AI/ML Engineer
Experience: 5-8 Years
Location: Gurgaon/Chennai(Remote)
Notice Period: Immediate to 15 days
Budget:11-14LPA
Mandatory Skills:AWS (SageMaker, S3, Glue, Kinesis, ECS, EKS), Python, Kubernetes & Docker, Kafka, FastAPI / Flask, Azure DevOps / AWS DevOps, Terraform / CloudFormation,ML deployment, automation & scalable data pipelines
Job Summary
We are looking for a skilled AI/ML Engineer with strong expertise in cloud engineering, DevOps practices, and machine learning operations. The ideal candidate will have hands-on experience in deploying, monitoring, and scaling ML models in production environments along with building robust data pipelines and automation frameworks.
This role requires a blend of ML engineering, cloud infrastructure, and DevOps capabilities to enable efficient and scalable AI solutions.
Key Responsibilities
- Design, develop, and deploy scalable machine learning models in production environments
- Build and maintain automated ML pipelines and workflows
- Develop and manage data pipelines (ETL/ELT) for large-scale data processing
- Implement CI/CD pipelines for ML and application deployment
- Work with cross-functional teams to integrate ML solutions into business applications
- Monitor model performance and ensure reliability, scalability, and accuracy
- Develop APIs for ML services using frameworks like FastAPI or Flask
- Implement event-driven architectures and streaming solutions
- Automate infrastructure provisioning using Infrastructure as Code (IaC) tools
- Optimize cloud resources and ensure cost-effective deployments
Required Skills
- 5+ years of experience in Cloud Engineering, DevOps, or ML Engineering
- Strong hands-on experience with AWS services such as:
- SageMaker
- S3
- Glue
- Kinesis
- ECS / EKS
- Proficiency in Python for automation, scripting, and API development
- Experience with Kubernetes and container orchestration
- Strong understanding of ML model deployment and monitoring
- Knowledge of event-driven architectures and streaming tools like Kafka
- Experience with CI/CD pipelines using Azure DevOps or AWS DevOps tools
- Hands-on experience in building data pipelines (ETL/ELT workflows)
- Experience in developing APIs using FastAPI / Flask
- Familiarity with Infrastructure as Code (Terraform, CloudFormation, etc.)
Preferred Qualifications
- Experience working in multi-cloud environments
- Exposure to MLOps frameworks and tools
- Strong understanding of distributed systems and microservices architecture
- Experience in performance tuning and optimization of ML systems
Pay: Up to ₹1,600,000.00 per year
Work Location: Remote
