Senior Machine Learning Engineer - Kubogent
Aivar Innovations (company site, opens in a new tab)4–8 yrsBengaluruOn-siteDirect career pageEst. 18–35 LPA
Posted on 8 Sept
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Job description
Structured overview of role & requirements
About This Role
- Develop and maintain Kubogent's machine learning model training and inference capabilities, including reusable training jobs and fine-tuning workflows.
- Own end-to-end ML workflows: data preparation, training, evaluation, experiment tracking, model lifecycle management, and production-grade pipeline implementation.
- Collaborate closely with platform engineers to integrate ML workflows into Kubogent's Kubernetes-based infrastructure and shape product features and APIs based on ML operations.
Minimum Requirements
- 4-8 years of hands-on experience in machine learning engineering with substantial practice in training and fine-tuning models, including large language models.
- Strong Python programming skills with experience in mainstream ML frameworks such as PyTorch or TensorFlow.
- Experience with MLOps tooling like MLflow covering experiment tracking, model versioning, and reproducibility.
- Experience working with real-world data: cleaning, transformation, dataset preparation, and validation.
Ideal Candidate Profile
- Experienced in developing production-grade ML systems that integrate training, inference, and lifecycle management within Kubernetes environments.
- Comfortable with advanced ML workflows encompassing distributed training, model evaluation pipelines, and performance optimization at scale.
- Capable of translating experimental ML research into maintainable, repeatable platform-level capabilities for other engineering teams.