As a Senior Advanced AI Engineer at Honeywell, you will be a driving force in designing, developing, and deploying end-to-end cloud and AI/ML solutions aimed at bringing autonomous capabilities to Honeywell products over the next decade. You will operate as a hands-on technical leader, working on everything from data pipelines to model optimization and drift detection, while mentoring junior team members to build a truly full-stack AI/ML practice.
ResponsibilitiesKey Responsibilities- Design and implement high-impact AI/ML models and workflows, ability to work on Cloud architectures and build solutions, ensuring scalability and reliability on cloud platforms such as Databricks, VertexAI, etc.
- Collaborate with cross-functional teams (Data Engineering, ML Engineering, DevOps) to create holistic MLOps pipelines, leveraging frameworks such as MLflow and Kubeflow.
- Conduct thorough reviews of ML models for performance, bias, and drift, proposing corrective actions.
- Integrate AI (including TimeSeries, Computer Vision, NLP, GenAI/RAG/Agentic AI) solutions into existing Honeywell products, maintaining rigorous code quality standards.
- Mentor junior engineers, promoting best practices in model development and deployment.
- Bachelor’s or Master’s degree in Computer Science, AI, or related technical field.
- 6+ years of hands-on experience developing and deploying ML models in production.
- Proven track record in advanced machine learning frameworks (e.g., TensorFlow, PyTorch).
- Demonstrated expertise in MLOps tools and best practices (CI/CD, containerization, orchestration).
- Strong Python skills, with exposure to additional languages (Scala, Java), considered a plus.
- Full-stack AI/ML experience (data ingestion through model deployment and maintenance).
- Strong analytical mindset with a bias towards skeptical, data-driven decision-making.
- Familiarity with cloud platforms (AWS, Azure, or GCP) for large-scale training and deployment.
- Ability to communicate technical concepts to both experts and laypersons.
- Knowledge of Agile or similar software development methodologies.
Skills Required
- Bachelor's or Master's degree in Computer Science, AI, or a related technical field
- 6+ years of hands-on experience developing and deploying machine learning models in production
- Experience with advanced machine learning frameworks such as TensorFlow or PyTorch
- Expertise in MLOps tools and practices, including CI/CD, containerization, and orchestration
- Strong Python programming skills
- Full-stack AI/ML experience from data ingestion through model deployment and maintenance
- Familiarity with AWS, Azure, or GCP cloud platforms
- Exposure to Scala or Java
- Ability to communicate technical concepts to technical and nontechnical audiences
- Knowledge of Agile or similar software development methodologies
Honeywell Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Honeywell and has not been reviewed or approved by Honeywell.
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Retirement Support — Retirement benefits are anchored by a strong 401(k) match with clear vesting and annual funding mechanics. Plan administration and education resources further reinforce long‑term savings support.
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Leave & Time Off Breadth — Time away provisions include company holidays, flexible vacation for many exempt roles, and paid sick time. These policies contribute meaningful breadth beyond base pay.
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Parental & Family Support — Paid parental leave is available to all parents with flexible usage options, and certain family‑building supports are included. Birth mothers can coordinate leave with short‑term disability for extended coverage.
Honeywell Insights
What We Do
Honeywell is a Fortune 500 company that invents and manufactures technologies to address tough challenges linked to global macrotrends such as safety, security, and energy. With approximately 110,000 employees worldwide, including more than 19,000 engineers and scientists, we have an unrelenting focus on quality, delivery, value, and technology in everything we make and do.









