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Ml data associate-ii, artificial general intelligence – data services (agi – ds)

Cambridge
Evi Technologies Limited
Service
€60,000 - €80,000 a year
Posted: 22h ago
Offer description

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ML Data Associate-II, Artificial General Intelligence – Data Services (AGI – DS), Cambridge

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Client:

Evi Technologies Limited


Location:

Cambridge, United Kingdom


Job Category:

Other

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EU work permit required:

Yes

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Job Reference:


Job Views:

14


Posted:

22.06.2025


Expiry Date:

06.08.2025

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Job Description:

AI is the most transformational technology of our time, capable of tackling some of humanity’s most challenging problems. Amazon is investing in generative AI and the responsible development and deployment of large language models (LLMs) across all of our businesses. Come build the future of human-technology interaction with us.
We are looking for those candidates who just don’t think out of the box, but make the box they are in ‘Bigger’. The future is now, do you want to be a part of it? Then read on!


Key job responsibilities
•Maintain and follow strict confidentiality as customer privacy is our biggest tenet
• Work with a range of different types of data including but not limited to text, speech, image, and video
• Deliver high-quality labelled data, using guidelines provided to meet our KPIs and using in-house tools and software
• Assume the role of a subject matter expert for Machine Learning (ML) data workflows and demonstrate proficiency in researching, creating factually and grammatically correct responses, ranking responses, creating grammatically correct text, speech, image, video annotation.
• Ability to make logical decisions while performing tasks even when provided information is ambiguous.
• Eye for detail and ability to pivot from one category of requirement to another instantaneously.
• Demonstrate support for daily operational deliverables like AHT, quality, TAT for multiple task types assigned to you and the team
• Demonstrate expertise in handling end to end data execution process related to labelling the tasks and be less dependent on work instructions
• Contribute to root cause analysis, identify error patterns and identify solutions to improve quality of labelling tasks
• Responsible for identifying day-to-day process and operational issues in SOP, tools and suggest changes to unblock operations
• Demonstrate ownership in floor support to clarify internal queries during execution on need basis


A day in the life
We are looking for a ML Data Associate (MLDA) to undertake the task of foundational labeling functions, such as dialogue evaluation on speech, text, audio, video data, to assess and improve Alexa’s performance in everyday situations.
Your ability to concentrate, multi-task and your high attention to detail helps you deliver high-quality work as well as maintaining strict confidentiality and follow all applicable Amazon policies for securing confidential information. You will be a part of a diverse team with the shared vision to make huge strides in the world of technology and the way we use Artificial Intelligence. An inner drive, individuality, and a creative mind are extremely beneficial.


About the team
The team works strictly in the office Monday through Friday with an eight-hour shift. We are constantly looking for ways to improve our capabilities and deliver the best product possible. Diverse team, regular meetings, trainings, and Amazon events throughout the year await you.

BASIC QUALIFICATIONS

• Fluent proficiency in English language, including grammar and spelling (both written and verbal).
• Comfortable working with speech from various dialects and accents of one or more of the following regional languages: English
• High-School or equivalent diploma.
• 2+ years of professional work experience with demonstrated task execution ability
• Excellent computer skills, including MS Office, with good typing speed (> 50 wpm and above)
• Ability to effectively write and evaluate diverse subject matter across various domains
• Proven capacity to leverage open-source resources effectively for comprehensive research purposes
• Ability to adapt well to fast-paced environments with changing circumstances, direction, and strategy
• A sense of ownership and drive and a willingness to accept the challenge of daily deadlines is essential


PREFERRED QUALIFICATIONS

• Bachelor’s degree in a relevant field or equivalent professional experience.
• Familiarity with content management may be beneficial
• Exposure to US culture/communication, prior experience in Machine learning domain will be an added advantage
• Ability to work across multiple teams and multi-task on programs


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