Skywise Engineer

Bangalore Area
Full-time
Posted Nov 15, 2026

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Skills

AWS
CI/CD
Google Cloud
Large Language Models
Machine Learning
Microsoft Azure
Python
SQL

Job description

Job Description:

Description

We are seeking an experienced and highly analytical Data & AI Specialist to join our team. In this role, you will be instrumental in designing, building, and operationalizing machine learning models and scalable data architectures. Beyond technical execution, this role requires exceptional stakeholder management and communication skills to bridge the gap between complex AI capabilities and strategic business objectives. You will partner with cross-functional leaders to identify opportunities where data and artificial intelligence can drive measurable value, optimize processes, and enhance our product offerings.

Job Responsibilities

•Design, develop, and deploy end-to-end Machine Learning and AI solutions (including traditional ML, deep learning, and Generative AI) to solve complex business problems.

•Act as the primary liaison between the Data/AI team and business units, translating non-technical business requirements into clearly defined data science problems.

•Build and maintain robust, scalable data pipelines to extract, transform, and load (ETL) data from diverse sources.

•Manage expectations, timelines, and deliverables with executive sponsors and project stakeholders.

•Present complex analytical findings, model performance metrics, and strategic recommendations to non-technical audiences clearly and compellingly.

•Lead cross-functional workshops and meetings to evangelize AI capabilities and identify new use cases across the organization.

•Optimize ML models for performance, scalability, and deployment in production environments (MLOps).

•Collaborate closely with software engineers, product managers, and data analysts to integrate AI features into enterprise applications.

Job Qualifications

•Experience: 4 to 8 years of proven experience in Data Science, Data Engineering, AI/ML development, or a closely related field.

•Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, Data Science, or a related quantitative discipline.

•Technical Skills:

•Advanced proficiency in Python and SQL.

•Strong understanding of statistical modeling, predictive analytics, NLP, and deep learning (TensorFlow, PyTorch, or Scikit-Learn).

•Hands-on experience with cloud platforms (AWS, Google Cloud, or Azure) and big data technologies.

•Experience with model deployment, monitoring, and CI/CD pipelines (MLOps).

•Communication Skills: Ability to articulate technical constraints, opportunities, and outcomes to business stakeholders in plain language.

•Stakeholder Management: Proven track record of successfully navigating organizational dynamics, building consensus, and managing cross-functional projects.

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.

Company:

Airbus India Private Limited

Employment Type:

Permanent -------

Experience Level:

Professional

Job Family:

Digital

By submitting your CV or application you are consenting to Airbus using and storing information about you for monitoring purposes relating to your application or future employment. This information will only be used by Airbus.

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. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom airbus.com .

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.