Position Details
About this role
This role focuses on building and maintaining scalable ML infrastructure, including training, evaluation, and deployment workflows for large-scale models.
Key Responsibilities
- Lead ML infrastructure development
- Build training and evaluation pipelines
- Implement feedback-driven learning systems
- Optimize distributed training workflows
- Ensure operational excellence
Technical Overview
The environment involves Python, ML pipelines, distributed systems, and infrastructure for training orchestration, evaluation, and feedback loops.
Ideal Candidate
The ideal candidate is a senior ML engineer with over 5 years of experience in software engineering and ML systems, skilled in Python and large-scale ML pipelines. They have expertise in training orchestration, model evaluation, and deploying feedback-driven ML workflows, with strong leadership and collaboration skills.
Must-Have Skills
Nice-to-Have Skills
Tools & Platforms
Required Skills
Hard Skills
Soft Skills
Industry & Role
Keywords for Your Resume
Deal Breakers
Less than 5 years of experience in ML or software engineering, Lack of proficiency in Python, No experience with ML pipelines or distributed systems
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