Whenever a customer visits Amazon and types in a query or browses through product categories, Amazon Search services go to work.
Human Labeled Data (HLD) organization helps Search services in providing a better customer search experience by delivering quality data annotation to help improve AI/ML models driving these services.
Our vision is to create business value by delivering high quality data at scale.
We look to provide easy and scalable labeling solutions to support search that are high quality, cost efficient, and secure.
Our vision is to enable improvement in the search experience for our customers, by accurately determining labels for products targeted by the search queries received.
We collaborate closely with several machine learning (ML) applied science teams that develop and test ML models to improve the quality of semantic matching, ranking, computer vision, image processing, and augmented reality.
To support our vision, we need exceptionally talented, bright, and driven people.
Duties will include ensuring that standards for productivity and quality assurance are met by your team, taking part in planning, organizing and directing the work of subordinates or others, outlining procedures and instructions on work received, making time estimates on new jobs received, ensuring utilization of team is high, mentoring and training new/existing team members.
If you have what it takes then this is your chance to work hard, have fun, and make history.
Key job responsibilitiesAs a Lead Data Specialist, ML Data Ops, you will be responsible for meeting operational and business goals overlooking about 30-40 associates, having expertise in one or more processes/functions and proficient in English.
You will also be a driving initiative across sites for process improvements, SoP and guidelines formulation, diving deep to provide data insights as and when required.
Your key responsibilities will include (but not limited to) the below:
The candidate actively seeks to understand Amazon's core business values and initiatives, and translates those into everyday practices.
Some of the key result areas include, but not limited to:
Experience in managing process and operational escalationsDriving appropriate data oriented analysis, adoption of technology solutions and process improvement projects to achieve operational and business goalsManaging stakeholder communication across multiple lines of business on operational milestones, process changes and escalationsCommunicate and take the lead role in identifying gaps in process areas and work with all stakeholders to resolve the gapsBe a SME for the process and a referral point for peers and junior team membersHas the ability to drive business/operational metrics through quantitative decision making, and adoption of different tools and resourcesAbility to meet deadlines in a fast paced work environment driven by complex software systems and processesAbility to perform deep dives in the process and come up with process improvement solutions through automationShall collaborate effectively with other teams and subject matter experts (SMEs), Language Engineers (LaEs) to support launches of new processes and servicesBASIC QUALIFICATIONS- A Bachelor's Degree and relevant experience of 2+ years as a subject matter expert or similar.
- Intermediate knowledge and hands on experience with MS Excel
- Excellent communication (written & oral) skills with the ability to curate responses for LLM development
- Experience in analytical, problem-solving, and critical-thinking skills
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Willingness to support several projects at one time, and to accept re-prioritization as necessary
- Demonstrated leadership with a bias towards action and ownership with strong organizational skills
PREFERRED QUALIFICATIONS- Experience with Artificial Intelligence interaction, such as prompt generation and open AI's
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Amazon is committed to a diverse and inclusive workplace.
Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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