MLOps Engineer (Freelancer)

Soul Ai; Hyderabad; Hybrid; INR 1,339,000 - 2,678,000; Part time

Benefits offered by this job

Top-tier pay

Contract/freelance work

Industry leaders in AI

Flexible work locations

Job summary

Soul AI is seeking an experienced MLOps Engineer to design and scale ML infrastructure using Kubeflow, MLflow, and SageMaker Pipelines. You will implement robust CI/CD workflows and automate ML lifecycles from feature engineering to deployment.

Candidates should have strong Python, TensorFlow, PyTorch, and cloud ML experience, plus monitoring with MLflow, Prometheus, Grafana. Remote/onsite options available in Hyderabad/Bangalore.

Qualifications

• Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines.
• Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
• Expertise in monitoring tools (MLflow, Prometheus, Grafana).
• Knowledge of distributed data processing (Spark, Kafka).
• Experience with A/B testing, canary deployments, serverless ML.

Responsibilities

• Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines.
• Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD).
• Automate ML workflows (feature engineering, retraining, deployment).
• Scale ML models with Docker, Kubernetes, Airflow.
• Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure).

Skills

Python

TensorFlow

PyTorch

CI/CD pipelines

Kubeflow

MLflow

Cloud ML platforms

Prometheus

Grafana

Spark

Kafka

Docker

Kubernetes

Airflow

Tools

GitHub Actions

Jenkins

GitLab CI/CD

AWS SageMaker

GCP Vertex AI

Azure ML

Job description

Are you an MLOps Engineer ready to take your expertise to the next level Soul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects.

Why Join.

• Above market-standard compensation.


• Contract-based or freelance opportunities (2\"12 months).


• Work with industry leaders solving real AI challenges.


• Flexible work locations- Remote | Onsite | Hyderabad/Bangalore.

Your Role.

• Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines.


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


• Automate ML workflows (feature engineering, retraining, deployment).


• Scale ML models with Docker, Kubernetes, Airflow.


• Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure).

Must Have.

• Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines.


• Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML).


• Expertise in monitoring tools (MLflow, Prometheus, Grafana).


• Knowledge of distributed data processing (Spark, Kafka).


• (Bonus


• Experience in A/B testing, canary deployments, serverless ML).