- Demonstrated experience in effectively defining optimal data creation strategies and executing them
- 2+ years of experience in ML data operations, with a strong understanding of data annotation/ML workflows and concepts
- Outstanding customer communication and management skills, especially in technical consultation
- Ability to translate complex technical concepts into tactical applications
- Bachelor's degree in Computer Science, Business or a related field
- Experience in project management
- Working knowledge of JSON, Command Line, and Python
- Technical account management experience
- Background in customer success or solution consulting
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
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. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Sunnyvale - 70,400.00 - 104,900.00 USD annually
As a Data Solutions Lead, you'll be the trusted advisor for our AGI-DS scientists, providing expert consultation on ML/Gen AI data collections and managing customer relationships. You'll drive business value through technical advisory and partnership building, creating and managing workstreams that delight our customers and deliver meaningful change for the models that back them.
Key job responsibilities
Drive and document effective ML/GenAI solutions for customer requests, transforming complex research objectives into clear, actionable data collection requirements
Coordinate across teams to ensure seamless delivery and stakeholder alignment
Own relationships with customer scientists, becoming their go-to partner for ML data solutions
Provide consultation on ML workflow capabilities, helping customers maximize value
Monitor and optimize collection health metrics to ensure customer success
Drive customer adoption through providing technical value and the provision of an exemplary customer experience.
You'll also:
Guide customers on workflow feasibility and data collection best practices
Collaborate with implementation teams to define and validate technical requirements
Evaluate scalability of annotation scenarios and provide strategic recommendations
Influence technical documentation and guidelines
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