Our senior developers excel in precise code-output annotation.
Scalable Solutions
Our on-demand service means you can scale up and down as needed.
White Glove Service
Sit back and relax while we take care of legal compliance and international payroll.
Join our clients
Our human data
Every developer in our network has undergone a rigorous vetting process and possesses at least 5 years of experience, ensuring your LLM will be trained by the best.
Combine our developers' deep knowledge of ML systems with our meticulous validation and quality checks for robust, scalable human data solutions.
Our weekly rolling contracts provide you with the flexibility to scale up and down to suit your needs. Pay-as-you-go for top quality human data, from LATAM's largest pool of pre-vetted developers.
Our validation processes ensure consistent quality control throughout your experience, whether you're looking for thousands or millions of data points.
We handle all human logistics for your LLM training, from sourcing and vetting top talent to managing and validating their work output, so you get clean data that's ready to use.
Plus, our complementary HR, compliance and payroll services make managing international teams a breeze.
Hire from our pool of 10,000+ senior, pre-vetted developers
As the largest pre-vetted talent platform in Latin America, we're confident we can find the perfect fit for you, from short-term project-based roles to permanent positions.
Yes! CloudDevs offers the chance to combine our developers' top-quality code and deep knowledge of ML systems with our meticulous validation and quality checks for robust, scalable human data solutions, perfect for training your LLM.
What is SFT code training?
Supervised Fine-Tuning, or SFT, is an approach to LLM training that curates a dataset of high-quality LLM outputs in order to fine-tune the model using a standard language modeling objective. SFT is simple, affordable, and a vital tool for aligning language models.
What is RLHF code training?
Reinforcement Learning from Human Feedback, or RLHF, is a machine learning technique that utilizes human feedback to optimize ML models for more efficient self-learning. Reinforcement learning techniques train software to make decisions in order to maximize rewards, which can significantly improve their accuracy.
What is DPO code training?
Direct Preference Optimization, or DPO, is a method of aligning LLMs with human preferences without reinforcement learning. It directly trains the model on preference data which avoids the need for a separate reward model, making the training process more efficient.
How do you ensure quality code?
Our robust validation processes ensure consistent quality control throughout your experience, whether you're looking for thousands or millions of data points. Plus, every developer in our network has undergone a rigorous vetting process and possesses at least 5 years of experience, ensuring your LLM will be trained by the best.
How many years of experience do CloudDevs developers have?
All the developers who are accepted into the CloudDevs pool have at least 5 years of professional experience, with an average of 6 to 10 years. We also have a rich pool of CTOs, Tech Leads, Managers, and other senior professionals who average 15 to 20 years of experience.
Where are CloudDevs developers located?
Our developers are located across Latin America, with hubs in Brazil, Mexico, Argentina, and Colombia. These countries boast high English proficiency and a strong investment in technical infrastructure and higher education.
If you’re looking to hire outside of Latin America, we also have a dedicated global platform of developers across Europe and Asia. Get in touch to learn more!
Where have CloudDevs developers previously worked?
Our CloudDevs developers have worked for elite US companies including OpenAI, Microsoft, Google, Reddit, Dell, Calendly, Samsung, Venmo, PayPal, IBM, Disney and Airbnb.
Work with the best of the best from your industry – only at CloudDevs.