Devops Engineer- Gcp+Python

Programming & Development

Python: Advanced proficiency in Python development

Software Design: Ability to create maintainable, well-tested code with proper error handling

DevOps & Infrastructure

Containerization: Docker image building and optimization

Package Management: Creating and maintaining Python packages and dependencies

Orchestration: Experience with Kubernetes and/or RunAI

CI/CD: GitHub Actions workflow design and implementation

Cloud Platforms: GCP experience, particularly with tools like Cloud Batch or similar services

Resource Management: GPU allocation and workload optimization

Infrastructure Automation

Workflow Pipelines: Design and implementation of automated data workflows (processing, evaluation, deployment)

Artifact Management: Experience with versioning, storage, and metadata tracking for models or data artifacts

Data Versioning: Implementing dataset versioning and change management

Format Conversion: Knowledge of artifact optimization and format conversion (e.g., ONNX, TFLite, TensorRT, SNPE)

Additional Technologies [Optional]

API Development: Experience creating RESTful services and endpoints

Configuration Systems: Experience with Hydra or similar configuration frameworks

Experiment Tracking: Familiarity with W&B, MLflow, or similar tracking tools

Image Processing: Understanding of computer vision workflows and image handling tasks

Testing & Quality Assurance

Automated Testing: Unit, integration, and E2E test implementation for software systems

Performance Evaluation: Metrics calculation and performance benchmarking

Current Projects & Responsibilities

• Design and implement end-to-end deployment and monitoring pipelines
• Create automated workflows for data processing, quantization, conversion, and evaluation
• Develop version-controlled registries with comprehensive metadata capabilities
• Build systems for automated testing across multiple target architectures
• Implement robust data versioning and dataset management solutions
• Maintain CI/CD pipelines for software and system lifecycle management
• Optimize Docker environments for development and deployment
• Develop Python libraries and APIs for internal consumption