Machine Learning / MLOps Engineer

Job Description:

Role : Machine Learning / MLOps Engineer

Description

Airbus is looking for a MLOps Engineer to join in Bangalore, India, to design, build and deploy cutting-edge AI applications for Airbus Information Management (IM). You will be responsible for designing, implementing, and maintaining robust and scalable MLOps pipelines, focusing primarily on generative AI models deployed using services like Amazon SageMaker and Bedrock. Your expertise in containerization, CI/CD, and cloud infrastructure will be crucial for automating our model training, evaluation, deployment, and monitoring processes.

We seek out curious minds. We value attention to detail, and we care deeply about outcomes. We’re looking for passionate people, eager to learn, willing to share, establishing innovative ways of working and influencing culture change. Challenges are numerous and exciting. You will benefit from working with vibrant and diverse teams of IM, developing your skills through extensive dedicated training programs, the opportunity to travel and you will be empowered to make the difference!

This job requires the constant awareness of the compliance risks we face in day-to-day responsibilities. Continuous commitment to act with integrity with each other, with your communities, business partners and suppliers is the foundation of your success and sustainable growth.

Qualification & Experience

• Bachelor’s or Master's degree in Computer Science, Data Science, or a related field.

• Proven experience (2+ years) building and managing MLOps pipelines for machine learning models, preferably in a cloud environment (AWS preferred).

• Strong understanding of containerization technologies (Docker) and container orchestration platforms.

• Experience with AWS services such as SageMaker, Bedrock, EC2, S3, Lambda, and CloudWatch.

• Practical knowledge of CI/CD principles and tools.

• Experience working with large language models (LLMs).

• Excellent communication, collaboration, and problem-solving skills.

• Knowledge on software product cost, monitoring & optimization.

• Drive technical discussions and explain options/choices to technical and non-technical audience
  

Optional Skills

• Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.

• Familiarity with generative AI models and frameworks like LangChain.

• Experience with infrastructure-as-code tools like Terraform or CloudFormation.

• Knowledge of model monitoring and explainability techniques.

• Familiarity with various data storage and processing technologies.

• Experience with other cloud platforms (e.g. GCP).

• Contributions to open-source projects related to MLOps or machine learning.

Responsibilities

• Design, develop, and maintain robust MLOps pipelines for generative AI models on AWS, leveraging services like SageMaker, Bedrock, and other relevant AWS services.

• Implement CI/CD pipelines for automating model training, testing, and deployment workflows.

• Build and manage containerized environments using Docker for reproducible and scalable model deployment.

• Develop and implement monitoring and logging solutions to track model performance, identify potential issues, and ensure high availability.

• Collaborate with data scientists and machine learning engineers to optimize model training and inference performance.

• Research and evaluate new MLOps tools and techniques to improve the efficiency and effectiveness of our workflows.

• Contribute to infrastructure-as-code initiatives, ensuring the reliability and scalability of our cloud infrastructure.

• Participate in code reviews and ensure adherence to best practices for software development and MLOps.

• Support troubleshooting and resolution of production issues related to model deployment and infrastructure.
  

Success Metrics

Success will be measured in a variety of areas, including but not limited to

• Delivering solutions on time, meeting large-scale enterprise standards and quality requirements

• Bring innovative and cost effective solutions

• Achieve customer satisfaction

Airbus is proud to be an equal opportunity employer and is committed to create an inclusive and diverse work environment. AGI selects job applicants (internal and external) on the basis of suitability for the job, and irrespective of gender, marital status, age, sexual orientation, gender identity or expression, nationality, religion, ethnicity or different abled/ (dis)ability.

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.

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