MLOps Engineer (Freelancer)

Soul Ai; New Delhi; Hybrid; INR 2,500,000 - 5,500,000; Full time

Benefits offered by this job

Premium compensation

Flexible contracts

Remote & hybrid opportunities

Exclusive AI talent pool

Job summary

Soul AI in India is seeking talented MLOps Engineers for contract and freelance roles to work on high-impact AI projects. You will build and automate end-to-end ML pipelines, deploy models, and ensure performance observability across cloud platforms.

Flexible remote and hybrid options are available in Hyderabad and Bangalore. Ideal candidates have strong Python, TensorFlow, PyTorch and MLOps tooling experience, plus hands-on exposure to cloud ML services and data-versioning tools.

Qualifications

• Strong expertise in Python, TensorFlow, PyTorch, MLOps tools.
• Hands-on with AWS/GCP/Azure ML
• Experience in data versioning (DVC, Delta Lake)
• Understanding of distributed data processing (Spark, Kafka)

Responsibilities

• Build & automate ML pipelines using Kubeflow, MLflow, Airflow
• Develop CI/CD pipelines (GitHub Actions, Jenkins, GitLab)
• Deploy ML models with Docker, Kubernetes, and cloud ML platforms
• Optimize model performance & ensure observability (Evidently AI, Grafana, Prometheus)

Skills

Python

TensorFlow

PyTorch

MLOps tools

AWS/GCP/Azure ML

DVC

Delta Lake

Spark

Kafka

Serverless ML

Federated learning

A/B testing

Tools

Kubeflow

MLflow

Airflow

GitHub Actions

Jenkins

GitLab

Docker

Kubernetes

cloud ML platforms

Job description

Calling all MLOps Engineers! Looking to work on high-impact AI projectsSoul AI (by Deccan AI) is hiring Indias best talent for contract & freelance roles

• Whats in it for you


• Premium compensation (above market standards)


• Flexible contracts (2\"“12 months)


• Remote & hybrid opportunities(Hyderabad/Bangalore)


• Be part of an exclusive AI talent pool


• Your Responsibilities:


• Build & automate ML pipelines using Kubeflow, MLflow, Airflow


• Develop CI/CD pipelines (GitHub Actions, Jenkins, GitLab)


• Deploy ML models with Docker, Kubernetes, and cloud ML platforms


• Optimize model performance & ensure observability (Evidently AI, Grafana, Prometheus)


• Must-Have
  Skills:


• Strong expertise in Python, TensorFlow, PyTorch, MLOps tools


• Hands-on with AWS/GCP/Azure ML


• Experience in data versioning (DVC, Delta Lake)


• Understanding of distributed data processing (Spark, Kafka)


• BonusExperience with serverless ML, federated learning, A/B testing


• Ready to unlock top AI opportunities