
Data Science Professional
2 days ago
Job Overview
This role involves collaboration with research teams to prepare datasets for training and evaluation. It entails implementing and running model training workflows, including hyperparameter tuning, performing rigorous evaluation of models against benchmark datasets, building and maintaining pipelines for data preprocessing, feature extraction, and dataset versioning, as well as contributing to model deployment and monitoring in production environments.
- Key Responsibilities:
- Collaborate with research teams on dataset preparation and experimental workflows.
- Implement model training workflows, including hyperparameter tuning.
- Evaluate models against benchmark datasets.
- Built and maintain pipelines for data preprocessing, feature extraction, and dataset versioning.
- Contribute to model deployment and monitoring in production environments.
Requirements
- 2–5 years experience in machine learning engineering or applied data science.
- Strong programming skills in Python (PyTorch, TensorFlow, or equivalent).
- Experience with data wrangling and large dataset preparation.
- Collaboration with ML researchers on experimental workflows.
- Comfortable with cloud environments (AWS/GCP/Azure) and containerization (Docker).
About the Role
This is a challenging opportunity for experienced machine learning engineers to contribute to the development of innovative AI solutions.
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