About the position
The Customer Engagement Technology (CET) organization powers customer service by developing elegant customer and CS Associate (CSA) facing products globally. These products offer effortless self-service and automation solutions to our customers. If customers prefer to interact with a human, we enable CSAs to effectively and elegantly solve customers' issues using our associate-facing products powered through human-centered design. We are seeking a ML (Machine Learning) Quality Process Lead, who are fluent in Portuguese and English, to join the Omni Machine Learning Data Associate (MLDA) team within CET to help manage quality management processes to analyze, improve annotation, testing, and contact reading accuracy to support new feature and product launches for Customer Service Large Language Models (LLMs).
Responsibilities
- Review annotations by paying close attention to details, making necessary adjustments to ensure high-quality data that supports ongoing model improvement.
- Perform root cause analysis using basic data analysis in Excel and SageMaker (annotation tool) on annotations to identify opportunities for improving data accuracy.
- Provide support for ML model training data annotations, assisting annotators in maintaining high-quality work by enforcing best practices.
- Improve Standard Operating Procedures (SOPs) by sharing findings from reviews or deep dives, ensuring a consistent standard of excellence across the team.
- Review LLM testing results provided by testers, paying close attention to details, to ensure their accuracy and identify areas for improvement.
- Carefully monitor the accuracy of multiple annotation projects and proactively communicate any blockers or potential delays in the completion of quality checks.
Requirements
- Language fluency in Portuguese (Native-level) and English.
- Experience in creating and managing ML annotation processes, testing models, and quality assurance methodologies.
- Analytical and problem-solving skills to identify patterns, inconsistencies, and areas for improvement.
- Ability to thoroughly investigate and identify misalignment between annotations and SOPs, as well as the root causes of inaccuracies.
- Strong ownership and accountability to meet SLAs, and proactive communication regarding blockers, and proposed solutions.
- Ability to collaborate closely with cross-functional teams, understand project/stakeholder requirements, and align annotation efforts and model testing accordingly.
Nice-to-haves
- Bachelor's Degree
- Experience in annotation
- Familiarity in using Excel
- Experience with project management and stakeholder management
Benefits
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
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