MLops Engineer

5 days ago

Hyderabad, Telangana, India Orbion Infotech Full time ₹ 12,00,000 - ₹ 24,00,000 per year

Industry & Sector:
Technology services firm operating in the Enterprise AI, Machine Learning Platform and Cloud Infrastructure sector. We build and operate production-grade ML systems and data platforms that enable analytics, predictive automation, and intelligent products for B2B customers.

Role: MLOps Engineer (On-site, Noida, India)

We are hiring a hands-on MLOps Engineer to join an on-site engineering team in Noida. You will own the end-to-end lifecycle for ML models — from reliable training pipelines to scalable, observable production deployments — and work closely with Data Scientists, SREs, and platform teams to accelerate model delivery and operational excellence.

Role & Responsibilities

  • Design, build and maintain repeatable ML pipelines for training, validation and deployment using orchestration tools (e.g., Airflow, Kubeflow).
  • Containerize models and services and implement production deployments on Kubernetes with automated CI/CD workflows.
  • Implement model packaging and serving solutions (MLflow/Kubeflow/Seldon/BentoML) ensuring low-latency, scalable inference.
  • Automate infrastructure provisioning using Infrastructure-as-Code and manage cloud resources (AWS/GCP/Azure) for ML workloads.
  • Establish monitoring, alerting and model observability (metrics, drift detection, logging) to ensure SLA-driven performance.
  • Collaborate with Data Science to productionize feature engineering, reproducible training and automated retraining pipelines.

Skills & Qualifications
Must-Have

  • Proven hands-on experience with Python for ML productionization
  • Kubernetes
  • Docker
  • CI/CD (GitLab CI, Jenkins, or GitHub Actions)
  • MLflow or Kubeflow
  • AWS (or GCP/Azure) cloud services
  • Terraform (or equivalent IaC)
  • Airflow

Preferred

  • BentoML or Seldon
  • Prometheus
  • Feast (feature store) or Apache Spark

Other Qualifications

  • Minimum: 5 years of relevant experience in ML engineering, DevOps, or MLOps roles; must be willing to work on-site in Noida.
  • Experience collaborating with Data Scientists to convert experiments into production-grade services.
  • Strong debugging and system-design abilities; familiarity with model validation, A/B testing, and production monitoring.

Benefits & Culture Highlights

  • Fast-paced, product-driven engineering culture with strong focus on learning and technical ownership.
  • Opportunities for upskilling in cloud-native ML tooling and exposure to end-to-end ML platform design.
  • Competitive compensation, peer mentorship, and clear career progression for high performers.

To apply: candidates must be located in or willing to relocate to Noida and able to work on-site. This role is ideal for engineers who enjoy bridging Data Science and Cloud Engineering to deliver reliable, scalable ML products.

Skills: kubernetes,pipelines,python

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