Experienced Machine Learning Quality Process Lead - Customer Engagement Technology

Join arenaflex's Customer Engagement Technology (CET) organization, a dynamic team that powers customer service by developing elegant customer and CS Associate (CSA) facing products globally.

Location:

Virtual Location - Washington United States

Description:

At arenaflex, we're revolutionizing the way customers interact with our services. Our Customer Engagement Technology (CET) organization is at the forefront of this revolution, developing innovative products that 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're seeking an experienced Machine Learning Quality Process Lead, fluent in Portuguese and English, to join our Omni Machine Learning Data Associate (MLDA) team within CET. As a key member of this team, you'll play a crucial role in managing 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).

A Day in the Life:

As a Machine Learning Quality Process Lead, you'll be responsible for ensuring the highest quality data that supports ongoing model improvement. You'll review annotations, perform root cause analysis, and provide support for ML model training data annotations. Your expertise will help maintain high-quality work by enforcing best practices and improving Standard Operating Procedures (SOPs). You'll also review LLM testing results, monitor annotation project accuracy, and proactively communicate any blockers or potential delays in the completion of quality checks.

Key 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.

About the Team:

Our Omni MLDA team is a remote team that works together to develop and fine-tune generative AI machine learning models and executes testing plans to take the customer service experience to the next level. We collaborate closely with Science and Product/Program Management teams to release localized customer-facing and agent-facing CS solutions, allowing them to focus on the development of their new products. In addition, teams with existing CS experiences can rely on our team to keep their solutions up-to-date and push identified technical defects to tech partner teams or defect elimination teams.

Basic Qualifications:

* 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.

Preferred Qualifications:

* Bachelor's Degree

• Experience in annotation
• Familiarity in using Excel
• Experience with project management and stakeholder management

Benefits and Compensation:

At arenaflex, we offer a comprehensive benefits package that includes:

• Medical, Dental, and Vision Coverage
• Maternity and Parental Leave Options
• Paid Time Off (PTO)
• 401(k) Plan

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $40,400/year in our lowest geographic market up to $86,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. arenaflex is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Why Join arenaflex?

arenaflex is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

How to Apply:

If you're passionate about machine learning and customer engagement, and you're looking for a challenging and rewarding role, we encourage you to apply. Please submit your application via our internal or external career site. Apply To this Job Apply for this job Apply for this job