Sr Advanced Software Engr

Job description

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

Responsibilities

Key Responsibilities

Design and implement high-impact AI/ML models and workflows, ability to work on Cloud architectures and build solutions, 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.

Qualifications

Qualifications & Experience

Bachelor’s or Master’s degree in Computer Science, AI, or related technical field. 6+ 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.

Preferred Competencies

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.