Job Description & How to Apply Below
Quantum4U is a leading mobile app development company committed to enhancing global connectivity through innovative and scalable mobile applications. With a presence in the hands of over 70 million users worldwide, Quantum4U delivers top-tier utility apps that are secure, sustainable, and user-focused. The company offers comprehensive mobile app development solutions to businesses looking to establish a strong mobile presence and grow efficiently.
Backed by a global team, Quantum4U ensures the highest quality standards in the mobile app industry.
Location:
Gurgaon, Haryana
Experience:
6m
-3 yrs
Role Overview
We are looking for a full-time Junior Machine Learning Operations Engineer to support the deployment, monitoring, and reliability of AI/ML systems in production. This role is ideal for candidates who enjoy working at the intersection of machine learning, infrastructure, and Dev Ops . You will help ensure that AI models move smoothly from development to production with scalable and reliable infrastructure.
Key Responsibilities
Deploy AI/ML models into production environments
Build and maintain Dockerized AI services
Assist in setting up and managing CI/CD pipelines
Configure and manage CPU/GPU environments for model execution
Monitor model performance, system reliability, and uptime
Support debugging, logging, and optimization of deployed models
Required Qualifications
B.Tech / B.E. in Computer Science, IT, ECE, or a related field
Strong quantitative and logical reasoning skills
Working knowledge of Python and scripting
Solid understanding of Linux fundamentals
Hands-on experience with Docker
Must Have Skills
Strong Linux fundamentals
Hands-on Docker (image build, container run, docker-compose)
Basic CI/CD understanding
Python scripting
Model deployment understanding (how to expose model via API)
CPU/GPU environment basics
Git usage
Good to Have
Exposure to Kubernetes
Experience with MLflow or model tracking tools
Familiarity with AWS / GCP / Azure
Understanding of LLM deployment workflows
Who Should Apply
Candidates who enjoy hands-on infrastructure work
Learners who build and deploy projects, not just experiments
Engineers eager to grow in the MLOps domain
Experience Criteria
6–24 months of experience in Dev Ops / MLOps
OR
Strong academic or personal projects related to model deployment or infrastructure
Candidates with limited industry experience must provide Git Hub projects
Why Join Us?
Competitive salary
Professional growth opportunities
Fun, innovative work environment
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