We are seeking a highly skilled Machine Learning Engineer / MLOps Engineer to design, build, and deploy scalable machine learning systems. This role sits at the intersection of data science, software engineering, and DevOps, with a strong emphasis on productionizing models and maintaining robust ML pipelines.

Experience required - 6 - 8 years

Key Responsibilities
Design, develop, and deploy machine learning models at scale
Build and maintain end-to-end ML pipelines using up-to-date MLOps practices
Containerize applications and workflows using Docker
Orchestrate ML workflows with Kubeflow or similar platforms
Collaborate with data scientists to operationalize statistical and machine learning models
Implement CI/CD pipelines for ML systems and data workflows
Ensure reliability, scalability, and performance of ML infrastructure
Apply advanced statistical modeling techniques to solve complex business problems
Write clean, modular, and maintainable code using object-oriented programming principles
Monitor, evaluate, and continuously improve deployed models

Require Qualification
Bachelor's or Master's degree in Computer Science, Data Science, Statistics, or a related field
Robust experience in Machine Learning and Data Science




Solid understanding of Statistical Modeling and Advanced Statistics
Hands-on experience with Docker and containerized environments
Experience with Kubeflow or other ML orchestration tools (e.g., Airflow, MLflow)
Proficiency in at least one programming language (Python preferred)
Strong knowledge of Object-Oriented Programming (OOP)
Experience with CI/CD pipelines and DevOps practices
Familiarity with cloud platforms (GCP, or Azure)

Preferred Qualifications
Experience with large-scale distributed systems
Knowledge of feature stores, model versioning, and monitoring tools
Experience in deploying real-time or batch ML systems
Familiarity with infrastructure-as-code (e.g., Terraform)
Understanding of data engineering concepts and big data tools

Key Skills
Machine Learning & Deep Learning
MLOps & Model Lifecycle Management
Docker & Containerization
Kubeflow & Workflow Orchestration
Statistical Analysis & Advanced Modeling
Object-Oriented Programming
CI/CD & DevOps Practices

If you are interested in this chance, please click on the Apply Now button to submit your application.

📌 Ml Engineer Gujarat (India)
🏢 INX
📍 India