Machine Learning Operations Engineer

Airbus Group India Pvt Ltd; Bengaluru; On-site; INR 900,000 - 1,300,000; Full time

Job summary

Airbus India Private Limited seeks an entry-level MLOps Engineer in Bengaluru to help build and scale a centralized ModelOps platform. You will bridge software engineering, DevOps and ML operations to implement serverless APIs and robust deployment pipelines.

The role emphasizes Python, FastAPI, AWS services, and observability of model performance, latency and drift while collaborating with senior engineers on feature enhancements.

Qualifications

• Bachelor's or Master's degree in computer science, software engineering, information technology, data science or related field.
• 0-2 years hands-on experience in software engineering, DevOps, MLOps and cloud.
• Fresh graduates with strong project experience or internships are welcome.

Responsibilities

• Platform Operations & APIs: design, build and maintain high-performance, serverless microservices and RESTful APIs for model inference and operations.
• CI/CD & Pipeline Automation: configure robust pipelines using IaC and automate testing and deployment.
• MLOps & Model Management: deploy, monitor and manage ML and Generative AI models on AWS; observe drift and latency.

Skills

Python

FastAPI

Vue.js

AWS

AWS CDK

DevOps

Docker

GitHub CI/CD

Education

Bachelor's or Master's in Computer Science / Software Engineering / IT / Data Science

Tools

GitHub

GitLab

Jenkins

PostgreSQL

DynamoDB

AWS CDK

Job description

MLOps Engineer Job Description: At Airbus, we are harnessing the power of artificial intelligence to enhance efficiency and quality across our value chain. Our team is composed of technologists and business leaders dedicated to innovation and excellence. We are seeking a MLOps Engineer (0-2 Years of Experience) to join our Advanced Analytics and Artificial Intelligence PSL. Operating within a high-growth AI team, you will play a critical role in developing, maintaining, and scaling our centralized ModelOps platform. You will bridge software engineering, DevOps, and Machine Learning operations to ensure our AI infrastructure remains robust while independently executing feature enhancements. Working closely with senior engineers, you will focus on enhancing the ModelOps platform, helping to build MLOps deployment pipelines for both traditional Machine Learning and Generative AI models, exploring modern ML services, automating operational workflows, and building serverless internal tooling.

Qualifications & Experience

• Education: Bachelor's or Master's degree in Computer Science, Software Engineering, Information Technology, Data Science, or a related quantitative field.
• Experience: 0-2 years of hands-on experience in Software Engineering, DevOps, MLOps, and Cloud. Fresh graduates with strong project experience or internships in these areas are welcome to apply.

Key Responsibilities

• Platform Operations & APIs: Design, build, and maintain high-performance, serverless microservices and RESTful APIs for model inference and platform operations. Ensure high availability, reliability, and smooth day-to-day operations.
• CI/CD & Pipeline Automation: Build, configure, and maintain robust CI/CD pipelines (leveraging platforms like GitHub and GitLab) using Infrastructure-as-Code to automate testing and deployment. Implement automated checks to prevent operational downtime.
• MLOps & Model Management: Leverage native AWS AI/ML platforms to deploy, monitor, and manage the lifecycle of Machine Learning and Generative AI models. Set up basic observability for model drift, inference latency, and performance metrics.

Technical Requirements

• Core Programming: Strong proficiency in Python and hands-on experience with FastAPI. Basic knowledge of Vue.js (or similar modern JavaScript frameworks).
• Cloud & Infrastructure: Solid understanding of core AWS services (Lambda, S3, Sagemaker, Bedrock, IAM, ECS, API Gateway, etc.) and hands-on experience with AWS CDK for defining infrastructure as code.
• DevOps & Containerization: Practical experience creating and managing Docker containers, utilizing version control systems (GitHub, GitLab), and configuring deployment pipelines (e.g., using GitHub Actions, GitLab CI/CD, or Jenkins).
• Databases: Experience working with both relational (PostgreSQL) and NoSQL (AWS DynamoDB) databases.

Soft Skills & Behavioral Attributes

• Fast Learning Curve: Demonstrated ability to quickly master new technologies, tools, and frameworks.
• Adaptability & Agility: Willingness to wear multiple hats- building API one day and tweaking ML pipelines the next.
• Problem-Solving Mindset: Strong logical reasoning, analytical skills, and attention to detail.
• Communication: Clear written and verbal communication skills to articulate ideas effectively within a team environment.

Nice-to-Have / Added Advantages

• AWS or GCP Cloud certifications (e.g., AWS Certified Cloud Practitioner / Developer, GCP Associate Cloud Engineer).
• Active GitHub profile, Kaggle participation, or personal projects demonstrating end-to-end full-stack or computer vision implementations.
• AWS services like SageMaker and Step Functions.

Company: Airbus India Private Limited

Employment Type: Permanent

Experience Level: Entry Level

Job Family: Digital

Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief. Airbus is, and always has been, committed to equal opportunities for all.

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company's success, reputation and sustainable growth.