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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:
· Bachelor's 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:
· Master's 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.
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