Python for data Science AI ML
Key Responsibilities
Design develop and deploy scalable backend services using Python.
Build and maintain RESTful APIs using frameworks like FastAPI Flask or Django REST Framework.
Develop and integrate AI/ML models into production systems
Collaborate with data scientists DevOps and product teams to deliver end-to-end solutions.
Ensure code quality through unit testing CI/CD pipelines and Agile practices.
Monitor and troubleshoot production issues and performance bottlenecks.
Document development processes and maintain technical documentation.
Required Skills
Python: Advanced proficiency with clean modular coding practices.
REST API: Experience with API design documentation (Swagger/OpenAPI) and testing (Postman).
AI/ML:
Frameworks: TensorFlow PyTorch Scikit-learn
Techniques: Supervised/Unsupervised learning NLP Transformers
Tools: Hugging Face LangChain (for LLMs) MLOps pipelines
Cloud: Azure (preferred) AWS or GCP including services like Azure Functions App Services Blob Storage
DevOps: GitHub Actions Azure DevOps Docker Kubernetes.
Data: SQL PostgreSQL MongoDB Pandas NumPy.
Version Control: Git GitLab Bitbucket.
Python for data Science AI ML Key Responsibilities Design develop and deploy scalable backend services using Python. Build and maintain RESTful APIs using frameworks like FastAPI Flask or Django REST Framework. Develop and integrate AI/ML models into production systems Collaborate with data ...
Python for data Science AI ML
Key Responsibilities
Design develop and deploy scalable backend services using Python.
Build and maintain RESTful APIs using frameworks like FastAPI Flask or Django REST Framework.
Develop and integrate AI/ML models into production systems
Collaborate with data scientists DevOps and product teams to deliver end-to-end solutions.
Ensure code quality through unit testing CI/CD pipelines and Agile practices.
Monitor and troubleshoot production issues and performance bottlenecks.
Document development processes and maintain technical documentation.
Required Skills
Python: Advanced proficiency with clean modular coding practices.
REST API: Experience with API design documentation (Swagger/OpenAPI) and testing (Postman).
AI/ML:
Frameworks: TensorFlow PyTorch Scikit-learn
Techniques: Supervised/Unsupervised learning NLP Transformers
Tools: Hugging Face LangChain (for LLMs) MLOps pipelines
Cloud: Azure (preferred) AWS or GCP including services like Azure Functions App Services Blob Storage
DevOps: GitHub Actions Azure DevOps Docker Kubernetes.
Data: SQL PostgreSQL MongoDB Pandas NumPy.
Version Control: Git GitLab Bitbucket.
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