AI Engineer II (5613)

Honeywell; Missouri; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Health insurance

HSA

401(k) match

Paid time off

Flexible schedule

Tuition reimbursement

Certifications programs

Mission driven culture

Job summary

Honeywell seeks an AI/ML engineer to contribute to end-to-end design, development, and productionization of advanced AI solutions for manufacturing and enterprise use. You will build scalable models, production pipelines, and monitoring systems, working closely with data science partners and stakeholders to meet SLAs.

The role emphasizes disciplined software practices, CI/CD, and rapid deployment across frontend and backend systems, with on-site responsibilities and travel as needed.

Qualifications

• Bachelor's degree in a quantitative field.
• At least two years of relevant experience in computer science, data science, or related technical activities.
• Ability to travel as determined by the needs of the business.
• Ability to work on-site as directed by management and as determined by the needs of the business.
• Regular and reliable attendance is an essential function of this job.
• United States Citizenship; ability to obtain and maintain DOE security clearance if required for position.

Responsibilities

• Develop AI/ML models and algorithms using disciplined software-engineering practices, including version control, automated testing, and thorough documentation.
• Contribute to designing, building, and maintaining production-grade pipelines for model training, validation, deployment, and monitoring, applying CI/CD and modern orchestration and deployment practices.
• Optimize model performance for latency, throughput, and resource utilization to meet real-time manufacturing or business requirements.
• Collaborate with multiple stakeholders to translate business needs into AI system specifications, define service-level objectives, and provide technical guidance to data science partners.

Skills

Software engineering discipline

Communication skills

ML/DL concepts

Cloud platforms (Azure/AWS)

API development

Git/version control

CI/CD practices

Distributed data processing (Spark/Kak

Education

Bachelor's degree in quantitative field

Tools

Spark

Kafka

Azure

AWS

Git

Docker

Job description

Summary Contributes to the end-to-end design, development, productionization, and ongoing support of advanced artificial intelligence solutions for manufacturing or business applications, ensuring models are scalable, reliable, and seamlessly integrated into frontend and backend systems.

Duties and Responsibilities

• Develop AI/ML models and algorithms using disciplined software-engineering practices, including version control, automated testing, and thorough documentation.
• Contribute to designing, building, and maintaining production-grade pipelines for model training, validation, deployment, and monitoring, applying CI/CD and modern orchestration and deployment practices.
• Optimize model performance for latency, throughput, and resource utilization to meet real-time manufacturing or business requirements.
• Collaborate with multiple stakeholders to translate business needs into AI system specifications, define service-level objectives, and provide technical guidance to data science partners.

You Must Have

• Bachelors degree in quantitative field
• At least two years relevant experience in computer science, data science, or related technical activities
• Ability to travel as determined by the needs of the business
• Ability to work on-site as directed by management and as determined by the needs of the business
• Regular and reliable attendance is an essential function of this job
• United States Citizenship
• Ability to obtain and maintain, if required for position, a U.S. Department of Energy (DOE) security clearance (some positions require additional DOE designations)

We Value

• Ability to grasp complex technical and business problems, prioritize tasks, and devise innovative, production ready AI solutions that align with manufacturing or enterprise objectives.
• Demonstrated software engineering discipline: version control, unit/integration testing, continuous integration-continuous deployment (CI/CD), and documentation of code and system architecture.
• Strong communication skills (verbal, written, presentation) to convey technical concepts to stakeholders, collaborate with cross-functional teams, and produce clear technical specifications and run books.
• Deep knowledge of machine learning and deep learning concepts, including model design, training, evaluation, and optimization for performance, latency, and resource utilization.
• Familiarity with distributed data processing frameworks and big data ecosystems (e.g., Spark, Kafka) to support high throughput training and real time inference pipelines.
• Proven ability to create actionable visualizations or dashboards that surface model performance, data quality, and operational metrics for end users and decision makers.
• Experience with API development, microservices architecture, and version control systems (Git).
• Hands-on experience deploying AI applications on cloud platforms such as Azure or AWS.
• Solid understanding of Large Language Models (LLMs), Natural Language Processing (NLP), and Retrieval-Augmented Generation (RAG).

This job description is not all-inclusive; additional duties may be assigned. Employees must maintain regular, reliable attendance, and be able to work on-site and travel as needed.

What We Offer

• Medical, dental and vision insurance
• Health Savings Account (HSA)
• Industry leading 401(k) match
• Generous paid time off
• Flexible work schedule
• Tuition Reimbursement
• Professional Certification & License Programs
• Mission driven culture