At a Glance
- Tasks: Join us as a Senior Data Associate, labelling diverse data types for AI development.
- Company: Amazon is at the forefront of generative AI, transforming human-technology interaction.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and innovation.
- Why this job: Be part of a diverse team dedicated to improving lives through cutting-edge AI solutions.
- Qualifications: An Associate’s Degree or relevant experience; strong English skills and attention to detail required.
- Other info: Amazon values diversity and offers equal opportunities for all applicants.
The predicted salary is between 36000 - 60000 £ per year.
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 most important tenet.
- Work with a range of different types of data including, but not limited to: text, speech, audio, image, and video.
- Deliver high-quality labelled data, using guidelines provided to meet our KPIs and using in-house tools and software, as part of Amazon's commitment to developing and deploying AI responsibly.
- Demonstrate proficiency in generating high quality human insight data across a range of modalities, inclusive of text, image, video and audio.
- Capable of making sound judgments and logical decisions when faced with ambiguous or incomplete information while performing tasks.
- Eye for detail and ability to pivot from one category of requirement to another instantaneously.
- Demonstrate support on daily operational deliverables for multiple task types assigned to you and the team.
- Analyze root causes, identify error patterns, and propose solutions to enhance the quality of labeling tasks and their outputs.
- Responsible for identifying day-to-day process and operational issues in Standard Operating Procedure, tools and suggest changes to unblock operations.
- Demonstrate ownership in floor support to clarify internal queries during execution on need basis.
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. 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 of improving customers’ lives with practical, useful generative AI innovations. An inner drive, individuality, and a creative mind are extremely beneficial.
BASIC QUALIFICATIONS- An Associate’s Degree or related work experience.
- C1+ or equivalent fluency in English language.
- Strong business writing skills with ability to create reports, proposals, and professional correspondence.
- Advanced reading comprehension with ability to analyze complex business documents.
- Developed analytical thinking and structured problem-solving capabilities.
- Strong ability to interpret and implement detailed instructions across various projects.
- Proficient research skills with experience gathering and synthesizing information from multiple sources.
- Proven attention to detail in managing complex tasks and documents.
- Bachelor’s degree in a relevant field.
- 2+ years of professional work experience with demonstrated task execution ability.
- 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.
- 2-3 years project coordination or management experience (for support functions teams).
- Experience managing stakeholder relationships across departments.
- Advanced proficiency in Microsoft Office Suite and common business applications.
Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.
Senior Data Associate, Artificial General Intelligence – Data Services employer: Evi Technologies Limited - C67
Contact Detail:
Evi Technologies Limited - C67 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Associate, Artificial General Intelligence – Data Services
✨Tip Number 1
Familiarise yourself with the latest trends in generative AI and large language models. Understanding the technology and its applications will not only help you during interviews but also demonstrate your genuine interest in the field.
✨Tip Number 2
Showcase your analytical thinking and problem-solving skills by preparing examples from your past experiences. Be ready to discuss how you've tackled complex tasks or resolved issues, as this aligns closely with the responsibilities of the role.
✨Tip Number 3
Network with professionals in the AI and data services industry. Engaging with others can provide insights into the company culture and expectations, which can be invaluable when tailoring your approach for the interview.
✨Tip Number 4
Prepare to discuss your experience with various data types, such as text, audio, and video. Being able to articulate your familiarity with these modalities will set you apart as a candidate who is ready to contribute immediately.
We think you need these skills to ace Senior Data Associate, Artificial General Intelligence – Data Services
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Focus on your analytical thinking, attention to detail, and any experience with data handling or AI technologies.
Craft a Strong Cover Letter: In your cover letter, express your passion for AI and how you can contribute to Amazon's mission. Mention specific examples of your past work that demonstrate your ability to handle complex tasks and maintain confidentiality.
Showcase Your Writing Skills: Since strong business writing skills are essential for this role, include samples of reports or proposals you've written in the past. This will showcase your ability to communicate effectively and professionally.
Prepare for Potential Assessments: Be ready for assessments that may test your analytical skills and attention to detail. Practice by reviewing complex documents and summarising key points, as well as working on data interpretation exercises.
How to prepare for a job interview at Evi Technologies Limited - C67
✨Showcase Your Analytical Skills
As a Senior Data Associate, you'll need to demonstrate strong analytical thinking. Prepare examples from your past experiences where you've successfully analysed complex data or solved problems. This will show your ability to handle the responsibilities of the role.
✨Emphasise Attention to Detail
Given the importance of delivering high-quality labelled data, be ready to discuss how you ensure accuracy in your work. Share specific instances where your attention to detail made a significant difference in a project or task.
✨Demonstrate Adaptability
The job requires adapting to fast-paced environments and changing circumstances. Think of examples where you've successfully navigated changes in your previous roles, showcasing your flexibility and problem-solving skills.
✨Prepare for Technical Questions
Since the role involves working with various types of data, brush up on your technical knowledge related to data handling and labelling. Be prepared to answer questions about tools and software you’ve used, as well as your experience with different data modalities.