Key Responsibilities
- Develop and maintain scalable ML pipelines using Python and Scikit-Learn.
- Build and integrate LLM-based applications using LangChain and related frameworks.
- Design data workflows using Pandas NumPy and BigQuery for efficient data processing.
- Collaborate with cross-functional teams to deploy models and services in production.
- Optimize performance reliability and scalability of ML systems.
- Implement CI/CD pipelines for ML deployment and monitoring.
- Contribute to internal tooling and automation for model lifecycle management.
- Ensure compliance with data governance privacy and security standards.
Key Capabilities/Experience
- 5 years of professional experience in Python development with a strong focus on data and ML applications.
- 2 years of hands-on experience with LangChain and LLMs (e.g. VertexAI).
- 3 years working with Pandas NumPy and data manipulation techniques.
- 3 years of experience with Google BigQuery or similar cloud data platforms.
- 3 years of experience building ML models using Scikit-Learn including deployment and monitoring.
- Experience with Docker Kubernetes and CI/CD pipelines in production environments.
- Solid understanding of SQL and exposure to NoSQL systems.
- Familiarity with ML lifecycle tools (e.g. MLflow DVC) and software engineering best practices.
Required Experience:
IC
Key ResponsibilitiesDevelop and maintain scalable ML pipelines using Python and Scikit-Learn.Build and integrate LLM-based applications using LangChain and related frameworks.Design data workflows using Pandas NumPy and BigQuery for efficient data processing.Collaborate with cross-functional teams t...
Key Responsibilities
- Develop and maintain scalable ML pipelines using Python and Scikit-Learn.
- Build and integrate LLM-based applications using LangChain and related frameworks.
- Design data workflows using Pandas NumPy and BigQuery for efficient data processing.
- Collaborate with cross-functional teams to deploy models and services in production.
- Optimize performance reliability and scalability of ML systems.
- Implement CI/CD pipelines for ML deployment and monitoring.
- Contribute to internal tooling and automation for model lifecycle management.
- Ensure compliance with data governance privacy and security standards.
Key Capabilities/Experience
- 5 years of professional experience in Python development with a strong focus on data and ML applications.
- 2 years of hands-on experience with LangChain and LLMs (e.g. VertexAI).
- 3 years working with Pandas NumPy and data manipulation techniques.
- 3 years of experience with Google BigQuery or similar cloud data platforms.
- 3 years of experience building ML models using Scikit-Learn including deployment and monitoring.
- Experience with Docker Kubernetes and CI/CD pipelines in production environments.
- Solid understanding of SQL and exposure to NoSQL systems.
- Familiarity with ML lifecycle tools (e.g. MLflow DVC) and software engineering best practices.
Required Experience:
IC
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