As a Senior Advanced AI Engineer, you will design, develop, and deploy AI-driven solutions for smart buildings and industrial automation systems. Your primary focus will be building advanced ML models, integrating them into real-world control environments, and driving innovation across HVAC, lighting, security, and energy optimization. You will collaborate cross‑functionally, mentor junior engineers, and influence multiple projects with your technical expertise.
AI Solutions Design & Integration
- Design and integrate AI/ML models into Building Management Systems (BMS) and Industrial Control Systems (ICS), including SCADA and PLC environments.
- Implement real‑time API–based and batch‑inference workflows.
- Develop model feedback loops to support continuous learning and performance improvement.
- Build algorithms for real‑time decision‑making using sensor, IoT, and industrial process data.
Data Engineering
- Partner with Data Engineering teams on ETL workflows and data preparation for large‑scale building and industrial datasets (e.g., HVAC telemetry, energy consumption, machine performance).
- Contribute to feature engineering and ensure data readiness for modeling
- Support the development of training pipelines that leverage model registries and tracking systems.
Innovation & Research
- Explore emerging technologies such as generative AI, digital twins, multimodal foundation models, and autonomous control systems.
- Lead proof‑of‑concept initiatives and mentor junior engineers through early‑stage experimentation.
- Translate innovative concepts into practical solutions for automation and building intelligence.
Performance Optimization
- Collaborate with MLOps teams to optimize real-time inference across platforms (AKS, GKE, on‑prem microk8s).
- Work with production‑ready inference runtimes such as vLLM, ONNX Runtime, and NVIDIA Triton.
- Contribute to model conversion, quantization, and optimization for efficient inference.
- Partner with platform engineers on deployment strategies, scalability, and monitoring.
Compliance & Security
- Ensure all AI solutions comply with cybersecurity standards and industrial safety protocols.
- Maintain training and inference repositories to meet corporate and industry security requirements.
MUST HAVE
Technical Expertise
- Strong proficiency in Python and ML libraries such as PyTorch, TensorFlow, JAX, XGBoost, and scikit‑learn.
- Experience with Kubernetes, Databricks, or comparable platforms.
- Familiarity with CI/CD practices for AI/ML workflows.
- Working knowledge of PySpark for data exploration and pipeline contributions.
- Strong debugging, profiling, and performance engineering skills in Python.
AI/ML Knowledge
- Expertise in one or more key domains: NLP, time-series forecasting, computer vision, or reinforcement learning.
- Ability to build models with noisy or sparsely labeled datasets.
- Experience using MLflow or similar tools for tracking, reproducibility, and model registry.
- Knowledge of converting models for production inference (TorchScript, ONNX).
- Experience with model performance optimization (e.g., quantization, latency tuning).
- Working knowledge of applying, fine‑tuning, and optimizing foundation models for domain-specific tasks across text, vision, or time‑series modalities.
- Ability to make informed accuracy–cost trade-offs during model design.
Innovation Skills
- Ability to identify emerging AI trends and translate them into practical solutions.
- Experience in rapid prototyping, proof‑of‑concept development, and technology scouting.
- Strong problem‑solving mindset with a focus on creative and disruptive solutions.
Cloud & Edge Computing
- Knowledge of AI/ML offerings from major cloud providers (Azure, GCP, or AWS).
- Experience deploying AI/ML solutions on edge devices (e.g., NVIDIA Jetson) is a plus but not mandatory.
Education & Experience
- Bachelor’s degree in Computer Science, Electrical Engineering, or a related field; Master’s degree preferred.
- Bachelor’s + 6 years of relevant AI/ML experience
- Master’s + 4 years of relevant AI/ML experience
- PhD + 2 years of relevant AI/ML experience
WE VALUE
- Experience optimizing deep learning models for NVIDIA Jetson–based edge systems.
- Experience contributing to platform‑agnostic AI/ML solutions.
- Proven end‑to‑end ownership of the ML lifecycle, including training, deployment, and feedback loops.
- Experience with smart building platforms, SCADA systems, or energy management solutions.
- Demonstrated success delivering innovative AI solutions within automation domains.
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 information visit: Benefits at Honeywell
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. Job Posting Date: 03/27/2026.
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.