Orbion Infotech logo

MLops Engineer ( 5 Yrs Noida)

5 years

16 - 18 Lacs

hyderabad telangana india

Posted:1 day ago| Platform: Linkedin logo

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Skills Required

technology ai learning ml data analytics automation engineering training model design deployment orchestration airflow kubernetes packaging mlflow latency automate provisioning code aws gcp azure monitoring metrics drift logging python gitlab jenkins github terraform apache spark devops debugging testing tooling compensation

Work Mode

On-site

Job Type

Contractual

Job Description

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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