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Advanced Software Engr

Honeywell

Posted 25 Jun 2026

BengaluruHigh payGCC
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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

Responsibilities

  • Key Responsibilities

    • 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

Qualifications

  • Required Qualifications

    • 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