AI Engr II

As a AI Engineer II at Honeywell you will be a driving force in designing developing and deploying end-to-end 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.

Key Responsibilities

• Design and implement high-impact AI/ML models and workflows 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.

• 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.

4. Qualifications & Experience

• Bachelors or Masters degree in Computer Science AI or related technical field.
• 3 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.