MLOps Engineer

Why Join?

Above market-standard compensation

Contract-based or freelance opportunities (212 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)

(Bonus: Experience in A/B testing, canary deployments, serverless ML)