Team Lead - ML Data Management for Machine Translation
Santa Clara Valley (Cupertino), California, United States
Machine Learning and AI
The AI/ML machine translation team is looking for an exceptional ML data management team lead that is passionate about delighting the customer’s experience and pushing the envelope on machine learning, artificial intelligence, embedded and distributed computing.
- 5+ years of relevant work experience
- Familiarity with big data platforms and tooling (Hadoop, Hive, Pig, Spark, Solr, etc.)
- Familiarity with data visualization software (e.g. Tableau)
- Experience in building and evaluating ML models, preferably in the space of language tech.
- Excellent problem-solving and project management skills
- Excellent written and verbal communication skills
The ideal candidate for this position is hands-on with a proven track record for building successful teams and defining efficient processes that sit at the intersection of data management/engineering and machine learning (ML). A background in language technologies such as machine translation (MT) or speech recognition is strongly desired. The overall team responsibilities require close collaboration with many partner teams in the MT and the larger AI/ML organization to identify key requirements and to successfully deliver on solutions. The successful candidate for this leadership position therefore is a team player with excellent communication skills and a sound technical grasp. The team’s responsibilities touch on all aspects of data analysis and ML data management. They include metrics visualization, ML training/test data acquisition (usage logs, web crawls, licensing, etc.), curation (annotation, filtering, balancing to remove bias, etc.) and data set maintenance/indexing. In addition to extracting, transforming and maintaining data, its exploration in the context of ML model training pipelines is an important aspect and requires close coordination with respective ML research teams.
Education & Experience
MS in Data Science/Engineering, Computer Science or related fields