On-Site - Ai Data Annotator Apprentice (English Required)
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- Puerto Quito, Pichincha
- Permanente
- Tiempo completo
AI Data Annotator
to support the creation of high-quality datasets that
power real-world AI systems
.
This role is an entry point into
AI and machine learning workflows
, where you will build foundational skills in data quality, annotation, and structured processes that support production-grade systems. As part of our broader AI delivery pipeline, your work contributes to systems that continuously improve over time, not just one-time outputs.
You will work in a structured, collaborative,
in-office environment alongside engineers and technical leads
to produce accurate, consistent, and production-ready data used in computer vision, sports analytics, and robotics applications. Over time, this role can
grow into opportunities
in data quality, operations, and more advanced AI-related positions.
This is an entry-level, on-site role based in our Quito office.
IMPORTANT:
To be considered for this position, please attach your CV in English.
By applying to the job, you confirm you have read and accept our
Ecuador Privacy Notice
(also available at the bottom of this post). This is mandatory to be considered for our vacancy.
What You'll Do
Perform data annotation and labeling across images, video, and structured datasets
Label objects, events, and behaviors using clearly defined guidelines
Review and validate annotations to ensure accuracy, consistency, and completeness
Follow structured workflows designed for high-quality AI training data
Identify edge cases, ambiguous scenarios, and data inconsistencies
Escalate unclear cases and contribute to improving annotation guidelines
Collaborate with engineers and team leads to continuously improve dataset quality
Improve annotation speed and accuracy over time through feedback and repetition
Projects You May Work On
Computer Vision
Object detection and tracking
Video annotation and event labeling
Dataset preparation for model training and evaluation
Sports Analytics
Athlete tracking and motion labeling
Event detection (jumps, plays, movements)
Performance analysis datasets
Robotics & Sensor Systems
Scene and environment labeling
Multi-frame and multi-sensor annotation
Safety-critical dataset validation
A Professional level of English is required (B2)
Bachelor's degree in Computer Science, Information Technology, Mathematics, or a similar field
Strong attention to detail and consistency
Ability to follow structured instructions and guidelines precisely
Reliable, organized work habits
Willingness to learn and improve through feedback
Comfortable working with computers and web-based tools
Ability to work on-site in the Stack Builders Quito office
Nice to Have (Not Required)
Interest in AI, machine learning, or data systems
Experience with data entry, QA, or annotation tools
Familiarity with images, video, or digital media
What Success Looks Like
Create a substantial amount of annotations daily
High accuracy and consistency in labeled data
Strong attention to edge cases and ambiguity
Measurable improvement in speed and quality over time
Clear communication when something is unclear
Contributions to datasets that engineers can confidently use in production systems
What You'll Gain
Hands-on experience with AI and machine learning workflows
Exposure to real-world applications in computer vision, sports, and robotics
Experience working alongside engineers and technical teams
A strong foundation for future roles in data, QA, or AI-related fields
Why This Role Matters
AI systems are only as good as the data they learn from.
Your work directly impacts how models perform in real-world environments by ensuring the data is accurate, consistent, and reliable. This role is a key part of building AI systems that improve over time, not just once.
A certified
Great Place to Work
culture!
A
strong learning culture
with regular 1:1 sessions with your manager, and training.
Quarterly Employee Assessments Cycles
to keep track of your career advancement and skill development.
Top-tier
private health and dental insurance
.
Mental health assistance bonus
(subject to policy and after trial period).
7 days
of annual vacation, paid time off for sick days, and parental and family leave.
Quarterly virtual and in-person
team-building activities
, birthday and holiday celebrations, and other special events.
Exciting and impactful projects from different industries leveraging various
tools and technologies.
A
Welcome Package
on your first day with a Stack Builders laptop and additional equipment.
--
More than our EEO statement, this is what makes us a Great Place to Work:
Stack Builders is proud to be an equal opportunity employer. We are committed to creating a safe and inclusive work environment and don't tolerate discrimination or harassment during the hiring process or time of employment.
All team members and candidates are assessed and appreciated for their attitude, qualifications, and potential - regardless of race, religion, color, nationality, sexual orientation, gender expression or identity, age, disability, marital status, pregnancy, and other characteristics protected by law.
You can learn more about us by visiting our
website
, or taking a look at our
community content
.
--
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RUC:
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