Lead Python-based AI solution development from prototype to production, emphasizing code quality and maintainability.
Architect APIs and microservices that integrate AI models into existing and next-generation Honeywell platforms.
Drive unit testing, integration testing, and deployment workflows for robust, scalable AI applications.
Work closely with Data and ML Engineers to optimize data pipelines and model inference latency.
Oversee code reviews and enforce engineering best practices, ensuring reliability and clarity in all deliverables.
Key Skills and Qualifications
Bachelor’s or Master’s in Computer Science, Software Engineering, or a related field. Expert-level Python coding skills with a focus on identifying potential performance bottlenecks and strong background of software engineering experience, particularly in production-grade Python solutions.
Strong understanding of software engineering patterns, including microservices, RESTful APIs, and containerization, along with knowledge of DevOps and cloud-native architectures such as Docker and Kubernetes.
Experience with modern toolchains for Continuous Integration/Continuous Deployment (CI/CD), version control, and automated testing, ensuring efficient development processes.
Ability to mentor and coach others in clean coding, design patterns, and Pythonic practices, fostering skill development within teams.
Demonstrable history of building and deploying AI/ML applications at scale, with familiarity in libraries and frameworks such as FastAPI, Flask, TensorFlow, and PyTorch, and proven success in agile environments balancing speed with system robustness.
Our Offer
A culture that fosters inclusion, diversity, and innovation in an international work environment
Market specific training and ongoing personal development.
Experienced leaders to support your professional development