We are seeking a highly skilled Senior Advanced Software Engineer with deep expertise in computer vision, deep learning, and generative AI (GenAI). This role requires end-to-end ownership of machine learning pipelines, from research and prototyping to deployment and scaling in production environments. The ideal candidate will have profound knowledge of full-stack ML deployment and a proven track record of building robust, scalable systems.

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Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

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As a Sr Advanced Software Engr here at Honeywell, you will lead a team of software engineers, ensuring successful project execution and high-quality solutions. Collaborate with cross-functional teams to meet software engineering requirements.

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• Strong background in computer vision, deep learning, and GenAI frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
• Expertise in end-to-end ML pipeline development (data engineering, model training, deployment, monitoring).
• Expertise in deploying ML models to Edge ( x86, arm64 architectures )
• Proficiency in cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes).
• Solid understanding of MLOps practices (CI/CD, model versioning, monitoring, retraining).
• Experience with full-stack ML deployment including APIs, microservices, and scalable inference systems.
• Strong programming skills in Python, C++/Java, and modern ML toolchains.
• Excellent problem-solving, communication, and leadership skills.

Preferred Qualifications

• Experience with distributed training frameworks (Horovod, DeepSpeed).
• Knowledge of edge deployment for computer vision models.
• Familiarity with data pipelines (Spark, Kafka, Airflow).
• Contributions to open-source ML/AI projects.
• B.Tech/ M.Tech with 8+ years of experience

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• Architect and develop end-to-end ML pipelines for computer vision, deep learning, and GenAI use cases.
• Design scalable solutions for data ingestion, preprocessing, training, evaluation, and deployment.
• Implement and maintain full-stack ML deployment frameworks across cloud and on-prem environments.
• Automate CI/CD workflows for ML models to ensure reproducibility and reliability.
• Monitor, troubleshoot, and optimize deployed models for performance, accuracy, and efficiency.
• Collaborate with cross-functional teams including data scientists, product managers, and DevOps engineers.
• Mentor junior engineers and contribute to technical knowledge sharing across the organization.
• Drive innovation by integrating emerging AI/ML technologies into production workflows.
• Optimize ML systems for large-scale data, distributed training, and high-throughput inference.
• Establish best practices for model versioning, monitoring, retraining, and lifecycle management