Python Unix machine learning Support Engineer
Must Have Technical/Functional Skills
Unix, ShellScripting, Python, Machine learning, Production Support
Roles & Responsibilities
• System Configuration: Configuring Unix systems to meet specific requirements and standards.
• Troubleshooting: Identifying and resolving issues with Unix systems and applications.
• Scripting: Automating repetitive tasks using Python scripts.
• Performance Optimization: Analyzing and improving the performance of Unix systems.
• Documentation: Creating and maintaining system documentation and guides.
• Collaboration: Working with other teams and departments to ensure Unix systems are integrated and functional.
• Implement AI workflows using Python, agent frameworks, and orchestration tools
• Develop LLM pipelines including prompt engineering, prompt chaining, memory, tool calling, and multi-agent coordination
• Integrate LLMs with enterprise systems and APIs
• These roles are essential for maintaining the reliability and efficiency of Unix-based systems, and Python skills
can be leveraged to automate and streamline these tasks.
• Designed, developed, and deployed machine learning models using supervised and unsupervised learning
techniques to solve real world business problems.
• Worked with Python ML libraries including Scikit learn, TensorFlow, PyTorch, Pandas, NumPy, and Matplotlib.
• Deployed models using REST APIs, Docker, or cloud platforms (AWS / Azure / Google Cloud Platform) to support production
use cases.
Salary Range- $110,000-$120,000 a year
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