:

- Design, build, and continuously improve CI/CD pipelines for both traditional backend services and ML workloads.

- Debug and resolve issues across ML pipelines—from data ingestion to model serving—working closely with the data science team.

- Develop and maintain Python-based backend services and tooling that support our ML infrastructure.

- Propose and implement MLOps automation solutions: model versioning, experiment tracking, automated retraining, monitoring.

- Manage cloud infrastructure (AWS/GCP/Azure), container orchestration (Docker, Kubernetes), and IaC tools (Terraform, Pulumi).

- Monitor production systems, set up alerting, and ensure high availability of ML-powered features.

- Collaborate with data scientists and backend engineers in an agile setting to ship reliable, scalable systems.

What you'll need:

- 2–3+ years of experience in DevOps, backend engineering, or MLOps roles.





- Strong Python skills—you can write production-grade backend code, not just scripts.

- Solid understanding of ML algorithms and workflows (training, evaluation, deployment)—enough to debug pipeline issues and have informed conversations with data scientists.

- Hands-on experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar).

- Experience with containerization (Docker) and orchestration (Kubernetes).

- Familiarity with ML tooling: MLflow, Kubeflow, Airflow, DVC, or equivalent.

- A proactive, ownership-driven mindset: you identify bottlenecks and propose solutions before being asked.

- Comfort with agile workflows and fast iteration cycles—you thrive in environments where priorities shift and quality still matters.

📌 Python Developer backend (only from product based ecommerce company) (India)
🏢 Talentquell
📍 India