MLOps Engineer (Freelancer)

Soul Ai; Chennai; Hybrid; INR 600,000 - 1,000,000; Part time

Benefits offered by this job

Remote work options

Contract-based opportunities

Job summary

Soul AI invites a skilled MLOps Engineer to shape our AI projects. You will architect and optimize ML infrastructure, build robust CI/CD pipelines, and automate ML workflows across cloud platforms.

Join a responsive team and work with leading AI experts on cutting-edge challenges, with flexible remote or onsite options in India.

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).
• Bonus experience in 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

Tools

Kubeflow

MLflow

SageMaker Pipelines

Docker

Kubernetes

Airflow

Prometheus

Grafana

Job description

AI Opportunities with Soul AIs Expert Community!

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

• Skills: 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).
• (BonusExperience in A/B testing, canary deployments, serverless ML).