Bengaluru, Karnataka

Job Summary

Required highly motivated individual who can work for the priorities of ART – AI Assisted Engineering team. The individual will be responsible for contributing to multiple advanced and disruptive technology projects with different stakeholders around the globe by adhering to Collins project execution practices. The individual will also be responsible for guiding the teams towards delivering successful AI solutions Proof of Concepts, Solution deployment, Technology Demonstrators and Current Product Development.

We are also looking for a candidate to have hands on experience in AI/ML technology development. The candidate should have a strong background in developing Gen AI applications and should have a good knowledge of processing structured and unstructured data. The candidate needs to be an active communicator and good team player.

Key Responsibilities

Develop projects to ensure maximum performance, providing purpose, direction, and motivation towards developing AI/ML applications at Collins Aerospace.

Participate and support on project activities such as requirements definition, architecture design, technology stack selection, development & deployment.

Identifying relevant AI/Gen AI technologies that can be leveraged for the use cases and build confidence with the customer early in the project through preliminary & critical design reviews.

Participate in appropriate client stakeholder’s reviews, providing day-to-day contact on project status and changes.

- Implement and optimize ML pipelines using MLflow, Kubeflow Pipelines, and TFX, enabling automated model training, validation, and deployment.

2.

Integrate

DevOps practices with Python scripting to automate infrastructure provisioning via Terraform, AWS CloudFormation, and Ansible for scalable ML environments.

- Configure and maintain CI/CD workflows using Jenkins, GitLab CI/CD, CircleCI, and GitHub Actions to streamline code integration and deployment for ML projects.




- Monitor and analyze ML system performance using Prometheus, Grafana, ELK Stack, and Fluentd, ensuring reliability and rapid issue resolution.
- Apply advanced proficiency in Git, GitHub, GitLab, and Bitbucket for source code management and collaboration within the development team.
- Participate in technical reviews, contribute to process compliance, and support feasibility studies by evaluating technical alternatives and risks for ML solutions.
- Prepare and submit project status reports, collaborating with internal stakeholders to define deliverables and minimize escalation risks.

Skill Requirements

Strong Software Development experience with AI/ML and Gen AI applications developed for Cloud or Embedded platforms. Good hands-on experience in Python programming language.

Good experience with Cloud Services, MLOps & AIOps including model deployment, CI/CD, model monitoring, data/model versioning, scalability, and productionizing AI solutions. Additionally, prior experience in developing AI/ML software for Aerospace industry is a plus.

Hands-on experience with Computer Vision technologies such as image classification, object detection, image segmentation, image processing, feature extraction.

Experience with OCR and intelligent document processing, including text detection, text recognition, document classification, information/entity extraction, document understanding, and processing of structured and unstructured documents.

Strong experience with at least one of the domains – Computer Vision, Natural Language Processing, Data Analytics,



with a reasonable understanding of the other two domains.

Prior

Experience in Generative AI & Agentic AI including prompt engineering, RAG, AI Agents, model evaluation and integration of foundation models/APIs.

Demonstrated strong interpersonal skills for influencing without authority.

Ability to communicate clearly and well, both verbally and in written form, developing strong partnerships across functions to drive measurable operational results.

Strong focus on quality and ability to navigate through company specific processes.

Ability to ensure alignment across multiple stakeholders both internally across several business units, and externally with third parties.

Excels in a fast-paced environment with high degree of accountability.

Diligent, disciplined, flexible, reliable, and strives for highest quality output.

1.

Advanced Proficiency In Ml

Ops, Including Mlflow, Kubeflow Pipelines, Tfx, And Metaflow.

2.

Advanced Proficiency In Devops Tools Such

As Terraform, Aws Cloudformation, Ansible, Jenkins, Gitlab Ci/Cd, Circleci, And Github Actions.

3.

Advanced Proficiency In Python For

Automation, Scripting, And Ml Pipeline Development.

4.

Advanced Proficiency In Monitoring And Logging

Tools: Prometheus, Grafana, Elk Stack, Fluentd.

5.

Advanced Proficiency In Version Control

Systems: Git, Github, Gitlab, Bitbucket.

6.

Solid Understanding Of Cloud Infrastructure And

Deployment Strategies.

7.

Solid Ability To

Troubleshoot, Optimize, And Maintain Ml Environments.

Other Requirements

1. Optional but valuable:

- AWS Certified Machine Learning � Specialty

3.

- Google Professional Machine Learning Enginee

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