Be part of a high-impact AI team driving innovation across Honeywells Smart Energy and Industrial Automation sectors.Work on cutting-edge projects like digital twins, predictive maintenance, and AI-powered grid optimization.

Access to enterprise-grade tools, training, and mentorship to accelerate your AI career.

We are seeking a highly skilled and innovative Advanced AI Data Science Engineer to join our AI/ML engineering team. This role is pivotal in designing, developing, and deploying scalable AI solutions that drive business transformation across industrial automation, smart energy, and connected utilities. You will collaborate with cross-functional teams to identify opportunities, build predictive models, and integrate AI into production systems.

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.

Key Responsibilities:

• Design and implement advanced machine learning models, including deep learning architectures, for predictive analytics, anomaly detection, and optimization.
• Collaborate with data engineers, product managers, and domain experts to define AI use cases and translate business problems into data science solutions.
• Lead the development of end-to-end AI pipelines, from data ingestion and preprocessing to model training, validation, and deployment.
• Apply techniques such as NLP, computer vision, and time-series forecasting to solve complex industrial problems.
• Contribute to the development of digital twins, edge AI, and real-time decision systems for smart grid and utility applications.
• Mentor junior data scientists and engineers, and contribute to internal AI knowledge-sharing initiatives.
• Ensure model explainability, fairness, and compliance with enterprise AI governance standards.

• Bachelors degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics
• At least 5 years of experience in Machine learning, or Data Science related with a strong portfolio of deployed models.
• At least 2 years of experience with AI.
• Proficiency in Python, TensorFlow/PyTorch, and cloud platforms.
• Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, Airflow).
• Strong understanding of data structures, algorithms, and software engineering principles.
• Familiarity with industrial IoT, SCADA systems, or utility industry is a plus.

• Experience with AutoML, generative AI, or reinforcement learning.
• Knowledge of cybersecurity and data privacy in AI systems.
• Ability to communicate complex technical concepts to non-technical stakeholders.
• Experience putting gen-AI solution in production
• Experience with frontier models and open source language models
• Experience with prompt design and prompt mangement
• Experience with tool usage including MCP
• Experience with popular frameworks like langgraph, crewAI
• experience with prompt evaluation and performance measurement of AI systems
• Experience debugging gen-AI solutions in production
• gen-AI usage in a big data environment
• gen-AI usage with quantitative data
• agentic workflows, including multi-agent communication, A2A protocol
• Databricks AI experience
• background in traditional AI/ML
• Azure AI experience

• Lead the development of complex AI solutions to address specific business needs, ensuring scalability, efficiency, and robustness
• Collaborate with crossfunctional teams to integrate AI solutions seamlessly into existing systems and processes
• Work directly with product managers and business leaders to understand requirements and align AI initiatives with overall business objectives
• Lead the endtoend AI development lifecycle, including project planning, resource allocation, and monitoring progress
• Provide mentorship and guidance to AI engineers, fostering a culture of continuous learning, innovation, and technical excellence