Hybrid Senior Advanced AI Engineer

at Honeywell

• Job title: Senior Advanced AI Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Cyber Security, ETL, Google Cloud Platform, IoT, Kubernetes, PySpark, Python, PyTorch, Tensorflow
• Location requirements: Hybrid, Atlanta, United States

About the role

• Senior Advanced AI Engineer at Honeywell focusing on AI-driven solutions for smart buildings and industrial automation. Collaborating cross-functionally and mentoring junior engineers.

Responsibilities

• 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
• 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
• 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
• Collaborate with MLOps teams to optimize real-time inference across platforms (AKS, GKE, on‑prem microk8s)
• Ensure all AI solutions comply with cybersecurity standards and industrial safety protocols

Requirements

• 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
• 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
• 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
• 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
• 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

Benefits

• Comprehensive benefits package including 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)
• 12 Paid Holidays