AI/ML Engineer 2

• 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 implement 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. 

• MS or Ph.D. in Computer Science, Software Engineering, Electrical Engineering, or related fields. 
• 3+ years of industry experience with Python in a programming intensive role. 
• 2+ years of experience with one or more of the following machine learning topics: classification, clustering, optimization, recommendation system, graph mining, deep learning. 
• 3+ years of industry experience with distributed computing frameworks such as Spark, Kubernetes ecosystem, etc. 
• 3+ years of industry experience with popular ml frameworks such as Spark MLlib, Keras, Tensorflow, PyTorch, HuggingFace Transformers and libraries (like scikit-learn, spacy, gensim, CoreNLP etc.). 
• 3+ years of industry experience with major cloud computing services. 
• Background or experience in building and scaling Generative AI Applications, specifically around frameworks like Langchain, PGVector, Pinecone, AzureML.  
• Experience with Prompt Engineering in Agent orchestration framework. 
• Prior experience in building data products and established a track record of innovation would be a big plus. 
• An effective communicator – you shall be an ambassador of Honeywell’s Machine Learning engineering at external forums and have the ability to explain technical concepts to a non-technical audience.  

• Proficient Python/PySpark coding experience 
• Proficient in containerization services 
• Proficient in Azure ML to deploy the models 
• Experience with working in CICD framework 
• Motivation to make downstream modelers’ work smoother 

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 .For more Honeywell Benefits information visit: 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.

Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. 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.