Advanced AI Engineer; Generative AI

Overview

Job Description The future is what you make it. When you join Honeywell, you become a member of our global team of thinkers, innovators, dreamers and doers who make the things that make the future. We are transforming from a traditional industrial company to a contemporary digital industrial business, harnessing the power of cloud, big data, analytics, Internet of Things, AI/ML, Automation and design thinking.

You will support change that brings value to our customers, partners, and shareholders through the creation of innovative software and data-driven products and services. You will help engineer contemporary applications and services, constructing solutions that remain scalable, adaptable and replicable, and you will be part of transforming Honeywell s IT organization through the delivery of technology products that will directly impact the company s growth.

You will be part of the IT Information Management & Analytics team and in this role, you will be at the forefront of implementing state-of-the-art Generative AI, Machine Learning and AI Cognitive Services to enhanced business use cases. This Advanced AI Engineer role will work with business stakeholders, IT business partners, functional consultants, and infrastructure/technology teams to deliver innovative AI technology solutions that accelerate digital transformation and drive operational efficiency as well as business growth.

You will focus on the full cycle delivery of AI/ML use cases from requirements/design to release, driving the evolution of AI/ML infrastructure/process, and enabling Intelligent Apps & Automation, next generation of AI Copilots/Assistants, etc.

You will report directly to our Sr. Director, AI and you’ll work out of our Phoenix, AZ location on a Hybrid work schedule.

Hybrid Work Schedule

Note:

For the first 90 days, New Hires must be prepared to work 100% onsite M-F.

• Develop and deploy advanced Generative AI large language models, Machine Learning and Deep Learning models/algorithms to enhance and/or automate existing business processes with predictive and intelligent decision making, content aggregation and contextualized insights.
• Collaborate with data scientists and data engineers to build production-level models and pipelines, including required preprocessing of input datasets and postprocessing after model inference.
• Process, cleanse and verify the integrity of structured and unstructured business data used for analysis.
• Analyze large amounts of information to discover underlying trends and patterns relevant for solving business problems. Select features and perform data transformation to optimize datasets for building models.
• Evaluate, visualize and communicate AI/ML model results and correlation with business KPIs.
• Work in a startup-type environment to design and build innovative applications using automation, machine learning/cognitive services, and scalable, production-ready solutions across a strategic business group.
• Actively lead, analyze and recommend highly complex business opportunities through assessments/workshops, detailed data analysis/modeling and end-to-end solutioning to propose predictive, AI-driven solutions that drive the most business value with sustained impact.
• Work within project planning constraints, communicate identified project risks and issues to the delivery/project manager and contribute to change control processes.
• Help develop standard operating practices and support the Operations Teams through UAT and after go-live.
• Continuously optimize existing AI/ML operations and help build an effective model performance monitoring, alert, and improvement framework to proactively identify problems before business impact.
• Partner and effectively communicate with Non-IT / Business users and stakeholders to understand the underlying business problem, and work with the extended team to define and communicate the right technical solution.

YOU MUST HAVE

• Bachelors in Computer Science, Data Science or Engineering fields
• Minimum 4 years of IT experience in solution architect / data scientist / software development for large corporate/organizations
• Hands-on experience in LLM engineering and LLMOps, including advanced prompt engineering and fine-tuning of LLMs
• Minimum 3 years of experience in building and deploying Machine Learning solutions using various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc
• Minimum 3 years of hands-on experience with Python programming and statistical packages, and ML libraries such as scikit-learn, Keras, Tensor Flow etc.
• Minimum 2 years of experience in building AI solutions with NLP/NLG frameworks such as Keras, Tensor Flow, Hugging Face Transformers and libraries like NLTK, Spacy, gensim
• Minimum 2 years of experience working on data science platform Databricks
• Minimum 2 years of experience in building IT use cases / solutions around AI/ML cognitive services, based on…