AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2) to consistently released new product innovations that set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Are you someone who cares about customer experience? Do you have a passion for Operations Management and Machine Learning? If so, then we're looking for you!
Amazon Web Services (AWS) is looking for a ML Data Associate III to join the Bedrock Data Team at AWS. As part of this team, you will be responsible for delivering high-quality training data to ensure the best performance of the AWS machine learning systems. Our goal is to produce the highest quality training data in the industry and to delight our customers by improving human language understanding and natural language processing.
The Bedrock team consists of data associates and content writers who primarily support the training of different models in the AWS generative AI platform. We specialize in text-based data annotation, writing for ML model training, and toxic content evaluation. Our work includes Responsible AI, Reinforcement Learning from Human Feedback, Supervised Fine Tuning, and Human Content Evaluation. Our team members bring a wealth of experience in fields like sociolinguistics, computational linguistics, syntax-semantics, and more.
Key job responsibilities
As an ML Data Associate III, you will demonstrate expertise in data workflows, collection methodologies, and analysis. You’ll work closely with stakeholders to ensure high-quality data annotation and continuous improvement. Your responsibilities include:
• Annotation and Data Collection: Work on annotation tasks, leveraging your understanding of ground truth requirements even in the absence of predefined guidelines. Provide clarification on annotation/data collection procedures to peers and stakeholders.
• ML Data Workflows and Analysis: Demonstrate expertise in ML data workflows and data collection methodologies. Identify trends and issues, perform deep dives, and provide impactful insights for stakeholders.
• Tool Optimization and Automation: Identify scope for automation and tool optimization to improve operational metrics. Work closely with engineering teams to influence the design and enhancements of tools.
• Process Documentation: Create and maintain scalable process documentation such as SOPs, data collection protocols, and training guidelines. Review and update existing SOPs periodically to ensure compliance and accuracy.
• Quality Assurance and Continuous Improvement: Perform quality checks on transactions/reviews performed by the ML data associates with precision. Contribute to process improvements by applying problem-solving methodologies and quality improvement tools.
• Stakeholder Collaboration: Collaborate with Program Managers, Data Scientists, and Engineers to define guidelines and tooling requirements. Review tool design documents and provide impactful suggestions for new processes.
• Escalation Management and Problem Solving: Handle escalations, conduct root cause analysis, and communicate key insights to stakeholders. Proactively address data curation and annotation issues to enhance overall quality.
• Coaching and Onboarding Support: Support the onboarding of new team members and coach them on process tasks. Provide feedback to the training team to customize training modules and facilitate skill development.
About the team
About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
• A Bachelor’s Degree and relevant experience as a subject matter expert or in a similar role.
• Intermediate knowledge and hands-on experience with MS Excel.
• Strong written & spoken communication skills.
• Strong attention to detail and the ability to successfully manage multiple competing priorities simultaneously.
• Knowledge of SQL, Python scripting, and Machine Learning.
• Understanding of quality-related concepts & tools such as 5Ys, 7 QC, F.M.E.A.
• Experience in e-commerce and online retail.
• Certified Six Sigma Green Belt.