Hands-On MLOps Engineer Crafting Scalable ML Solutions
Arkhya Tech. Inc.
About the role
About
Transform data into impactful ML solutions as an MLOps Engineer. Utilize Python and open-source tools to develop, deploy, and iterate end-to-end ML pipelines with a focus on performance and reliability.
In this hands‑on role, you will design and build ML models for various use cases. Collaboration with data engineering and platform teams is essential to leverage tools like Databricks and Spark for seamless scalability. Your expertise will drive model quality, improve efficiency, and ensure compliance with security standards.
Drive impactful ML solutions and enhance business decisions through your engineering prowess and data insights.
Key Responsibilities
- Design and develop diverse ML models
- Build robust ML pipelines in Python
- Implement rigorous evaluation and testing practices
- Operationalize MLOps with model tracking and monitoring
- Collaborate on API integrations for product systems
Requirements
- Strong Python software engineering skills required
- Proven experience deploying ML models in production
- Familiarity with ML libraries like TensorFlow or PyTorch
- Competence in SQL and data processing tools
- Experience with MLOps practices and tooling
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Requirements
- Strong Python software engineering skills required
- Proven experience deploying ML models in production
- Familiarity with ML libraries like TensorFlow or PyTorch
- Competence in SQL and data processing tools
- Experience with MLOps practices and tooling
Responsibilities
- Design and develop diverse ML models
- Build robust ML pipelines in Python
- Implement rigorous evaluation and testing practices
- Operationalize MLOps with model tracking and monitoring
- Collaborate on API integrations for product systems
Skills
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