Research Engineer AI developing modern applications using AI technologies for business solutions. Collaborating in a motivated team to advance AI vision with clean and maintainable code in Python.
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
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