Website Honeywell Technologies
Data Scientist II (GenAI & Computer Vision) — Honeywell Technologies
Company: Honeywell Technology Solutions (Honeywell Technologies)
Role Title: Data Scientist II
Location: Bengaluru, Karnataka, India
Work Mode: Hybrid / Office-Based
Employment Type: Full-Time
Experience Level: 3+ Years of professional experience building solutions using Machine Learning, Deep Learning, OCR, Computer Vision, and Generative AI models
Educational Requirement: Bachelor’s degree in Artificial Intelligence, Data Science, Computer Science,Statistics, Mathematics, or a related field (Master’s degree or PhD considered a strong asset)
Core Tool Stack: Python, SQL, Generative AI (GenAI), Large Language Models, OCR, Computer Vision (CV),AWS, Azure, MLOps, CI/CD Pipelines
Preferred Domain: Life Sciences, Industrial Automation, Manufacturing Data Systems
About Honeywell Technologies
Honeywell is a global Fortune 100 technology leader serving industrial, building automation, aerospace, and process sectors worldwide. Honeywell’s Technology Solutions (HTS) center in Bengaluru is a premier R&D hub that builds intelligent software solutions, IoT ecosystems, and advanced AI systems. Leveraging the Honeywell Forge intelligence layer, the Bengaluru data science team is driving the industrial sector’s transition from traditional automation to autonomous intelligence.
Role Overview
Honeywell is recruiting an experienced Data Scientist II to join its life sciences and advanced AI division in Bengaluru.
In this role, you will lead the design, development, and deployment of sophisticated machine learning models with a heavy emphasis on Generative AI (GenAI), Optical Character Recognition (OCR), and Computer Vision (CV). You will build end-to-end data and model pipelines, optimize inference workflows on cloud platforms (AWS/Azure), and deploy models following rigorous MLOps practices.
Key Responsibilities
Generative AI & Computer Vision Model Development
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GenAI & CV Implementation: Develop and implement advanced data science models covering text,image, data synthesis, and document intelligence for industrial systems.
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End-to-End Pipelines: Design, build, and maintain robust data and model pipelines, ensuring strict data integrity and scalable GenAI model deployment.
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Multimodal Integration: Collaborate with cross-functional software and product engineering teams to integrate GenAI and computer vision solutions into existing workflows.
Cloud Infrastructure & MLOps Operations
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Cloud Resource Scaling: Leverage enterprise cloud platforms (AWS and Azure) to provision scalable computing resources for intensive GenAI workloads.
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Production Deployment: Productionize AI/ML/GenAI solutions across both on-premises and cloud environments.
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MLOps Governance: Optimize and deploy machine learning models in accordance with established MLOps and CI/CD pipeline best practices.
Candidate Qualifications & Requirements
Required Qualifications
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Education: Bachelor’s degree in Artificial Intelligence, Data Science, Computer Science, Statistics,Mathematics, or a related quantitative discipline (Master’s degree or PhD preferred).
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Experience: 3+ years of hands-on professional experience building and deploying solutions using ML,DL, OCR, Computer Vision, and Generative AI models.
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Engineering Stack: High proficiency in Python and SQL.
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Cloud & MLOps: Proven experience with cloud platforms (AWS, Azure) and implementing CI/CD frameworks for model deployment.
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Communication: Excellent verbal and written communication skills to articulate complex AI concepts to cross-functional stakeholders.
Preferred Qualifications
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Hands-on exposure to knowledge graph technologies and advanced LLM frameworks.
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Prior domain experience in Life Sciences, pharmaceutical manufacturing, or industrial automation.
Role Summary
| Attribute | Details |
| Job Title | Data Scientist II |
| Company | Honeywell Technology Solutions |
| Location | Bengaluru, Karnataka, India (Hybrid Schedule) |
| Experience | 3+ Years |
| Primary Skill Stack | Python, SQL, Generative AI, Computer Vision, OCR, AWS, Azure, MLOps, CI/CD |
| Core Focus | End-to-End AI/GenAI Model Deployment, Life Sciences Systems, Cloud Scalability |
