Honeywell

Job Description

ABOUT HONEYWELL

Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the world’s most critical challenges around energy, safety, security, air travel, productivity, and global urbanization. We are a leading software-industrial company committed to introducing state-of-the-art technology solutions to improve efficiency, productivity, sustainability, and safety in high-growth businesses in broad-based, attractive industrial end markets. Our products and solutions enable a safer, more comfortable, and more productive world, enhancing the quality of life of people around the globe.

What you'll be doing:

• 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.

US Person requirements:

• Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. person, which is defined as, a US citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.

You Must Have:

• Bachelor’s degree from an accredited institution in a technical discipline such as the sciences, technology, engineering, or mathematics
• 7+ 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.
• 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.
• 2+ years of technical leadership leading junior engineers in a product development setting

Preferred Qualifications:

• 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.