Lead AI Engineer

Qualifications

• YOU MUST HAVE
• Bachelor’s degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics
• 6+ years of industry experience in writing production level, scalable code (e.g. in Python)
• 5+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, deep learning.
• 5+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc.
• 5+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, spacy, genism etc.).
• 5+ years of industry experience with major cloud computing services like Azure or GCP
• 1+ years of experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, AzureML, VertexAI
• Experience in building Agentic AI applications.
• 2+ years of technical leadership leading junior engineers in a product development setting
• WE VALUE
• An effective communicator – you shall be an ambassador of Honeywell’s Machine Learning engineering at external forums and can explain technical concepts to a non-technical audience.
• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields.
• Proficient Python/PySpark coding experience
• Proficient in containerization services
• Proficient in Azure ML or VertexAI to deploy the models
• Experience with working in CICD framework
• Motivation to make downstream modelers’ work smoother
• Prior experience in building data products and established a track record of innovation would be a big plus.
• BENEFITS OF WORKING FOR HONEYWELL
• In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. Learn more (https://benefits.honeywell.com/)
• The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: October 8, 2026.

ABOUT HONEYWELL TECHNOLOGIES

KEY RESPONSIBILITIES

• Collaborate with colleagues across multiple teams (Data Science and Data Engineering) on unique machine learning system challenges at scale.
• Leverage distributed training systems to build scalable machine learning pipelines for model training and deployments in IT/OT Products space.
• Design and implement solutions to optimize distributed training execution in terms of model hyperparameter optimization, model training/inference latency and system-level bottlenecks.
• Research and impalement state of the art LLM models for different business use cases including finetuning and serving the LLMs.
• Ensure ML Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design quality and monitoring.
• Optimize integration between popular machine learning libraries and cloud ML and data processing frameworks.
• Build Deep Learning models and algorithms with optimal parallelism and performance on CPUs/GPUs.