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Remote Machine Learning Enginer, Core Evaluations
grabjobsUnited States
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shift supervisor - Store# 04085, 5640 SPRING GARDEN ROAD
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StarbucksHalifax**Join us and inspire with every cup!**At Starbucks, itu2019s all about connection. People are at the heart of who we are, especially the people that are a part of our store team. We connect with each
shift supervisor - Store# 06149, GARDEN STONE PLACE
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Über
About the Role: We are seeking an experienced Machine Learning Engineer (MLE) to focus on audio model evaluation, specifically for speech generation and recognition models. This role involves designing and developing comprehensive model evaluation pipelines for both development and production environments, as well as creating automated dashboards for reporting evaluation results. As the founding member of our evaluation team, the ideal candidate is expected to leverage their experience to lead our evaluation efforts and play a key role in the future growth of the evaluation team.
What You’ll Do: Designing model evaluation pipelines for models in development and production
Designing user studies for subjective model evaluations.
Converting requirements into measurable metrics.
Designing and developing automated evaluation dashboard to see model performances and compare results.
Training new models to capture new and different evaluation metrics.
Communicating with the model team to help design better models based on the evaluation results.
Communicating with the data team to help decide the type of data necessary to improve model performance.
Communication with the product-manager to make sure product requirements are correctly measured.
Help grow the evaluation team as the founding member.
Lead the evaluation team in the future.
What You’ll Bring: Strong experience and intuition for designing metrics that capture model performance.
Strong experience with designing user studies on Mechanical Turk or similar platforms. .
Strong experience with model training and fine-tuning for model evaluation.
Strong statistical knowledge and experience to statistically compare evaluation results and take decisions.
Very strong engineering and programming skills.
Experience with training ASR, TTS models.
Experience at ML teams working on large-scale machine learning problems. (>3B models with >1m hours of data)
Sprachkenntnisse
- English
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