Data Quality Specialist – Portuguese (Brazilian or European)

Who are we?

Our mission is to scale intelligence to serve humanity. We’re training and deploying frontier models for developers and enterprises who are building AI systems to power magical experiences like semantic search, RAG, and agents. We believe that our work is instrumental to the widespread adoption of AI.

We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. We like to work hard and move fast to do what’s best for our customers.

Cohere is a team of researchers, engineers, designers, and more, who are passionate about their craft. Each person is the one of the best in the world at what they do. We believe that a diverse range of perspectives is a requirement for building great products.

Join us on our mission and shape the future!

Why this role?

We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans – by way of feedback. By labelling, ranking, auditing, and correcting text output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere is on the lookout for dynamic and dedicated Data Annotators with exceptional skills in Portuguese writing and translation.

Please Note: This is a part-time independent contractor position. We are looking for candidates who are able to commit to 20 hours minimum per week . This role is BYOD 💻 – Bring Your Own Device (laptop).

As a Data Quality Specialist, you will:
Label and Rank: Accurately label and rank machine learning data with advanced proficiency in Portuguese, ensuring data integrity and quality.
Audit and Correct: Scrutinize and rectify any inaccuracies in language data, maintaining the highest standard of data accuracy.
Reading and Text-Based Tasks: Efficiently complete reading and text-based assignments, with high attention to detail.
Preference-Based Tasks: Evaluate and complete tasks, assessing which responses in Portuguese best conform to our style guide.
Recommend Optimizations: Identify and suggest opportunities for improving data quality and model performance in Portuguese language tasks.
Provide Feedback: Collaborate and communicate effectively, providing feedback to cross-functional team members, particularly on Portuguese language-related matters.
Detail-Oriented Execution: Maintain meticulous attention to detail while performing repetitive and precise tasks, particularly when working with language data.
You may be a good fit if you have:
Language Proficiency: Native or near-native proficiency in Portuguese; excellent command over English.
Expert reading and writing skills – which you are ready to prove on our written test.
Strong attention to detail and commitment to accuracy – you’re the type to proofread all of your emails! 
High tolerance for repetitive and monotonous work.
Ability to follow complex instructions, navigate ambiguity and work independently.
Superb sense of urgency and time management.
Curiosity about technology and a knack for tackling problems in creative ways.
A reliable laptop you are able to bring into the office.
The Candidate Journey:
Initial Screening – Once you have submitted your application our Talent Team will review your resume and writing samples.
Virtual Meet & Greet – If selected to move forward, you will have a short video call with a member of our Annotation Army!
Practical Assessment – This assignment will test your written skill through various language-based tasks, such as a a writing sample, interacting with a chat bot, and more.
Offer – Independent Contractor Agreement.
Prospective candidates, please be advised: this role involves working with human generated and model generated tasks may involve exposure to not safe for work (NSFW) text content as part of data annotation tasks, including explicit, offensive, or other inappropriate material.