- Work from
- Worldwide
- Contract
- Full-time
- Experience
- Entry Level
- Posted
- 14 November 2026
- Apply by
- 13 January 2027
You will help develop and evaluate approaches that reduce token usage while maintaining strong output quality.
About the role
Join a machine learning team focused on improving large language model efficiency and quality.
Responsibilities
- Experiment with language model configurations to identify optimization opportunities.
- Build and maintain data pipelines for model training and evaluation workflows.
- Analyze performance metrics to assess model quality and efficiency.
- Contribute to internal tools that monitor and optimize model behavior.
- Follow current machine learning and language model research and apply relevant findings to product improvements.
Requirements
- A degree in computer science, data science, engineering, mathematics, or a related field, or equivalent practical experience.
- Hands-on experience building or training machine learning models with Python and frameworks such as PyTorch, TensorFlow, or scikit-learn.
- Knowledge of machine learning, statistics, model evaluation, and optimization techniques.
- Familiarity with large language models, natural language processing, and prompt design or tuning.
- Experience building machine learning data pipelines and analyzing model performance metrics.
- Experience contributing to tools or monitoring systems for tracking model performance is helpful.
Location
Remote, full-time.
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Discussion
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