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MLops Engineer
MLops Engineer

MLops Engineer at Deqode · Pune, Gurugram, Noida, Bhopal, Bengaluru (Bangalore) · 4 - 8 years · ₹8L - ₹22L / yr · Bootstrapped · Posted 13 May 2025

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MLops Engineer

Roshni Maji's profile picture
Posted by Roshni Maji
4 - 8 yrs
₹8L - ₹22L / yr
Pune, Gurugram, Noida, Bhopal, Bengaluru (Bangalore)
Skills
MLOps
skill iconAmazon Web Services (AWS)
AWS Sagemaker
skill iconPython

Role - MLops Engineer

Location - Pune, Gurgaon, Noida, Bhopal, Bangalore 

Mode - Hybrid


Role Overview

We are looking for an experienced MLOps Engineer to join our growing AI/ML team. You will be responsible for automating, monitoring, and managing machine learning workflows and infrastructure in production environments. This role is key to ensuring our AI solutions are scalable, reliable, and continuously improving.


Key Responsibilities

  • Design, build, and manage end-to-end ML pipelines, including model training, validation, deployment, and monitoring.
  • Collaborate with data scientists, software engineers, and DevOps teams to integrate ML models into production systems.
  • Develop and manage scalable infrastructure using AWS, particularly AWS Sagemaker.
  • Automate ML workflows using CI/CD best practices and tools.
  • Ensure model reproducibility, governance, and performance tracking.
  • Monitor deployed models for data drift, model decay, and performance metrics.
  • Implement robust versioning and model registry systems.
  • Apply security, performance, and compliance best practices across ML systems.
  • Contribute to documentation, knowledge sharing, and continuous improvement of our MLOps capabilities.


Required Skills & Qualifications

  • 4+ years of experience in Software Engineering or MLOps, preferably in a production environment.
  • Proven experience with AWS services, especially AWS Sagemaker for model development and deployment.
  • Working knowledge of AWS DataZone (preferred).
  • Strong programming skills in Python, with exposure to R, Scala, or Apache Spark.
  • Experience with ML model lifecycle management, version control, containerization (Docker), and orchestration tools (e.g., Kubernetes).
  • Familiarity with MLflow, Airflow, or similar pipeline/orchestration tools.
  • Experience integrating ML systems into CI/CD workflows using tools like Jenkins, GitHub Actions, or AWS CodePipeline.
  • Solid understanding of DevOps and cloud-native infrastructure practices.
  • Excellent problem-solving skills and the ability to work collaboratively across teams.


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About Deqode

Founded :
2016
Type :
Products & Services
Size :
100-1000
Stage :
Bootstrapped

About

At Deqode, our purpose is to help businesses solve complex problems using new-age technologies. We provide enterprise blockchain solutions to businesses.

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Mohini Bansal

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