Senior Engineer/Engineer - MLOps

Cielo Talent

7 - 12 years

20 - 35 Lacs

gurugram

Posted:None| Platform:

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Skills Required

mlops airflow ci/cd devops grafana jenkins bicep git docker terraform azure cloud aws kubernetes

Work Mode

Hybrid

Job Type

Full Time

Job Description

About this role:

MLOps Engineer

AWS

Key Responsibilities include:

Assist in building and maintaining ML pipelines for data preparation, training, testing, and deployment
Support the automation of model lifecycle tasks including versioning, packaging, and monitoring
Build and manage ML workloads on
AWS (SageMaker Unified studio, Bedrock, EKS, Lambda, S3, Athena)
and
Azure (Azure ML Foundry, AKS, ADF, Blob Storage)
Assist with containerizing ML models using
Docker
, and deploying using
Kubernetes
or cloud-native orchestrators
Manage infrastructure using IaC tools such as
Terraform
,
Bicep
, or
CloudFormation
Participate in implementing CI/CD pipelines for ML workflows using
GitHub Actions
,
Azure DevOps
, or
Jenkins
Contribute to testing frameworks for ML models and data validation (e.g., pytest, Great Expectations).
Ensure robust CI/CD pipelines and infrastructure as code (IaC) using tools like Terraform or CloudFormation
Participate in diagnosing issues related to model accuracy, latency, or infrastructure bottlenecks
Continuously improve knowledge of MLOps tools, ML frameworks, and cloud practices.

Required Qualification:

Bachelor's/Masters in Computer Science, Engineering, or related discipline
7 years+ in Devops, with 2+ years in MLOps.
Good Understanding of
MLflow
,
Airflow
,
FastAPI
,
Docker
,
Kubernetes
, and
Git
.
Proficient in Python and familiar with bash scripting
Exposure to MLOps platforms or tools such as SageMaker Studio, Azure ML, or GCP Vertex AI.

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