About Honeywell:

Honeywell is a Fortune 100 technology company that delivers industry-specific solutions that include aerospace products and services; control technologies for buildings and industry; and performance materials globally. Our technologies help aircraft, buildings, manufacturing plants, supply chains, and workers become more connected to make our world smarter, safer, and more sustainable. Join a team recognized for leadership, innovation, and diversity.

Role Summary:

We are seeking a motivated and skilled Software Engineer II to join our dynamic team. In this role, you will primarily focus on designing, developing, testing, and deploying robust Python-based APIs that serve as the backbone for integrating and managing Machine Learning (ML) models within Honeywells platforms and applications. You will leverage your software engineering expertise and understanding of the ML model lifecycle to build scalable, reliable, and efficient solutions.

Key Responsibilities:

Design, develop, test, deploy, and maintain high-quality, scalable, and secure Python-based RESTful APIs.

Collaborate closely with Data Scientists, ML Engineers, and Platform Engineers to understand requirements for integrating ML models.

Develop API endpoints and backend logic to support various ML model lifecycle management tasks, including:

o Model Training orchestration and monitoring.

o Implementing "Bring Your Own Model" (BYOML) capabilities.

o Facilitating Edge deployment workflows for ML models.

o Handling model conversion processes between different formats (e.g., TensorFlow SavedModel, ONNX, PyTorch JIT, TFLite).

Integrate APIs with existing cloud infrastructure, databases, and messaging systems.

Write clean, maintainable, well-documented, and testable code following best practices.

Participate in code reviews, design discussions, and contribute to improving development processes.

Troubleshoot and resolve issues related to API performance, reliability, and integration points.

Stay current with emerging trends and technologies in Python development, API design, MLOps, and relevant ML frameworks.

Contribute to the automation of deployment pipelines (CI/CD).

Basic Qualifications:

Bachelors degree in Computer Science, Software Engineering, or a related technical field.

3+ years of professional software development experience.

Minimum 2+ years of hands-on experience developing backend services and APIs using Python.

Proven experience with Python web frameworks such as Flask, FastAPI, or Django.

Solid understanding of RESTful API design principles and best practices.

Good knowledge of Machine Learning concepts and the typical ML model lifecycle (data prep, training, evaluation, deployment, monitoring).

Familiarity with ML frameworks like TensorFlow/Keras or PyTorch, particularly concerning model saving, loading, and serving.

Experience with version control systems, preferably Git.

Strong problem-solving and analytical skills.

Excellent communication and teamwork abilities.

Preferred Qualifications:

Masters degree in Computer Science or a related field.

Experience working with cloud platforms (e.g., Azure, AWS, GCP) and their ML services (e.g., Azure ML, SageMaker, Vertex AI).

Experience with containerization technologies like Docker and orchestration tools like Kubernetes.

Experience building and maintaining CI/CD pipelines (e.g., Jenkins, Azure DevOps, GitLab CI, GitHub Actions).

Hands-on experience specifically implementing solutions for BYOML, Edge deployment, or model conversion.

Knowledge of MLOps principles and tools (e.g., MLflow, Kubeflow).

Experience with relational (SQL) and/or NoSQL databases.

Familiarity with asynchronous programming in Python (e.g., asyncio).

Experience working in an Agile/Scrum development environment.

Experience in industrial IoT or related domains.