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4.7 OUT OF 5
2,500+ companies use Revelo to scale their engineering capacity

400k+

VETTED SOFTWARE
ENGINEERS

14 days

average time
to hire

100+

TECHNOLOGIES
COVERED

30-50%

savings over
US hires

Hire the top 1% of

Machine Learning

engineers

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Alexandre C.
Back-end Developer
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8 years
of experience
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Fluent in English
Python
Java
Rust
React.js
Amazon Redshift
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Andres R.
Back-end Developer
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8 years
of experience
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Fluent in English
Go
Scala
Node.js
PHP
PostgreSQL
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Mateus O.
Data Developer
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8 years
of experience
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Fluent in English
Python
Machine Learning
Analytics
SQL
Data Modeling
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Evelyn E.
DevOps
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7 years
of experience
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Fluent in English
MySQL
AWS
JIRA
C++
Java
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Diego S.
Back-end Developer
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7 years
of experience
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Fluent in English
PHP
Python
Scala
Ruby
Cython
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Juan M.
Back-end Developer
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6 years
of experience
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Fluent in English
Python
PHP
React.js
Ruby
Cloud Cost Reduction
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Isadora F.
Front-end Developer
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11 years
of experience
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Fluent in English
Node.js
React.js
Next.js
Linux
Angular
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Cesar R.
Fullstack Developer
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11 years
of experience
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Fluent in English
PHP
React.js
C#
Android
JavaScript

WHY HIRE DEVELOPERS THROUGH REVELO?

Finding world-class developers shouldn't mean sacrificing quality for speed or breaking your budget to access top talent. Revelo connects you with rigorously vetted senior developers from Latin America who work in your timezone and integrate seamlessly with your existing team.


Whether you're scaling a startup or augmenting an enterprise engineering team, our human-vetted talent network and in-market recruiting experts deliver pre-screened candidates who are ready to contribute from day one.

LET REVELO HELP YOU HIRE YOUR NEXT WORLD-CLASS DEVELOPER

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2,500+ companies have trusted Revelo to build their engineering teams
400,000+ pre-vetted developers in our talent network
Hire in as few as 14 days
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Share Your Requirements
Tell us what you're building and what kind of developer you need. Skills, experience level, team dynamics. You set the bar, we find people who clear it.
2
Meet Vetted Candidates
Within days, you're talking to developers we've already vetted for the skills that matter. No wading through hundreds of profiles. Just qualified people ready to talk.
3
Interview Your Favorites
Run your own technical interviews. Ask the hard questions. See how they think. We've done the screening, now you decide if they're the right fit for your team.
4
Hire and Onboard
Make the offer. We handle payroll, compliance, taxes, and benefits so you can focus on building. Your new developer starts strong from day one.

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SOFTWARE DEVELOPERS IN 
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2,500+ companies trust REVELO with their tech hiring needs

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James O'Brien
Co-Founder & COO at Ducky.ai
Revelo delivered exactly what we were looking for. We went from reviewing 40 resumes to interviewing just 6 qualified candidates, and our new engineer was shipping code within two weeks.
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Heather Townsend
Co-Founder & COO at Cabana
The quality of engineers in South America is amazing. We needed full-time people who would truly commit to our team and culture, and that's exactly what we got.
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Charlie Hill
Co-Founder & Chief Product Officer at Harbor
We now have four Revelo engineers who are essential to our team. We wouldn't be where we are without them.
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Revelo rated Best Relationship in Freelance Platforms on G2, Spring 2026Revelo named Mid-Market Leader in Freelance Platforms on G2, Spring 2026Revelo named Momentum Leader in Freelance Platforms on G2, Spring 2026Revelo rated Easiest To Do Business With in Freelance Platforms on G2, Winter 2026Revelo rated High Performer for Small Business in Freelance Platforms on G2, Spring 2026Revelo named Leader in Freelance Platforms on G2, Spring 2026
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Tips for Hiring Machine Learning engineers

Machine learning (ML) engineers are experts who construct, test, design, and optimize artificial intelligence (AI). They can train models with data and use the models to automate processes like speech recognition, image classification, and market forecasting.

However, finding a suitable machine learning developer can be challenging. Although many machine learning engineers are on the market, only some have the skills, personality, and values that fit your company.

Read this guide to learn about machine learning development, what machine learning engineers do, their typical salary range, and how to write job descriptions and interview questions to attract and hire a machine learning engineer who can propel your business forward.

What Is Machine Learning?

Developers optimize a machine learning algorithm (mathematical model) during machine learning development to find certain outputs and patterns from a large dataset. The result of this process is a machine-learning model.

The three main types of machine learning techniques are:

  1. Supervised machine learning: This provides the algorithm with an input dataset and optimizes it for a certain output. Engineers often use supervised machine learning in image recognition.
  2. Unsupervised machine learning: This offers the algorithm an input dataset but does not optimize or reward it for specific outcomes. Instead, it trains the algorithm to group objects according to common characteristics. Online stores' recommendation engines often use unsupervised machine learning.
  3. Reinforcement learning: This instructs the algorithm to train itself using many test experiments. This happens when the algorithm continuously interacts with the environment rather than relying on training data. One common example of reinforcement learning is self-driving vehicles (autonomous driving).

There are many applications for machine learning models, including:

  • Image recognition
  • Stock price prediction
  • Wine quality prediction
  • Iris classification
  • Breast cancer prediction
  • Music recommendation systems
  • House pricing prediction
  • Social media sentiment analysis
  • Loan eligibility prediction

What Does a Machine Learning Engineer Do?

Machine learning engineer responsibilities may vary depending on the company and project. However, most roles require machine learning software engineers to handle the following tasks regularly:

  • Research, create, and develop algorithms for machine learning
  • Assess and organize data
  • Execute experiments and tests
  • Observe and optimize machine learning processes to develop robust machine learning systems
  • Translate business and client objects into machine-learning models
  • Define data augmentation pipelines
  • Deploy machine learning models to assist production
  • Analyze machine learning models' errors and create strategies to overcome them

Machine Learning Engineer Salary

According to Glassdoor, the average mid-level machine learning engineer with four to six years of experience in the U.S. earns $136,385 annually.

While ML engineers in Latin American countries are equally skilled, their lower cost of living means they usually earn 30% to 50% less than their U.S. counterparts, with salaries varying based on location and experience. Revelo can help you hire the best remote ML engineers, all highly qualified, pre-vetted Latin American developers, offering a cost-effective solution without compromising quality.

How to Write a Job Description for Machine Learning Engineers

A compelling and engaging job description or advertisement is key to attracting the best candidates. At a minimum, provide a concise and accurate job description that describes the role and the required experience level.

You can determine the role's experience level by looking at the responsibilities and skills. Junior or entry-level machine learning developers only have zero to three years of professional machine learning experience, tend to have fewer specialized skills, and require mentoring from more experienced colleagues. Mid-level machine learning developers have four to six years of experience, possess more specialized skills, and provide mentoring to junior and entry-level devs. Finally, senior machine learning experts have over six years of experience, specialized skills (including honed mentorship skills), and managerial duties.

Your job description should also include the following sections:

  • Company information: Tell job seekers about your brand, values, culture, and preferred project management methodology (i.e., Scrum, Agile, or Waterfall). This will help you attract like-minded candidates.
  • Required education, experience, and qualifications: Tell readers what education, experience, and qualifications your role requires. Most employers require machine learning hires to have at least a bachelor of science in computer science, data science, or a related field, proficiency with programming languages like Python, expertise in visualizing and manipulating large datasets, and familiarity with Linux.
  • Job duties: List the hire's day-to-day responsibilities. Be as clear as possible — you want to give applicants an idea of what it's like to work for you.
  • Compensation and benefits: List the salary range and benefits for this position. Competitive salaries and job benefits are more likely to attract high-quality talent. Consider including benefits such as free gym memberships, work-from-home opportunities, and health insurance.

Interview Questions for Machine Learning Engineers

Ince you've sifted through the best candidates, you must ask thoughtful and informative interview questions to assess candidates' technical and soft skills, discuss best practices for the engineer job, and learn more about their drive, experience, values, and community involvement. Here are some sample questions to get you started.

Why did you become a machine learning engineer?

This question reveals an applicant's motivation for becoming a machine learning developer. A good answer should demonstrate the applicant's:

  • Passion for machine learning development
  • Machine learning education and qualifications
  • Technical knowledge, such as programming and machine learning model training skills
  • Favorite machine learning applications and projects

What programming languages are you familiar with?

This question demonstrates job seekers' technical knowledge. Top machine learning engineers should know at least three of the following languages:

  • Python
  • R
  • Java
  • JavaScript
  • C++
  • LISP
  • Julia

What are the three stages of building a machine-learning model?

Ask this question to evaluate prospective hires' knowledge of machine learning models. A strong answer should look something like this:

The three stages of creating a machine learning model are:

  1. Model building involves picking a suitable algorithm for a model and training it according to requirements.
  2. Model testing is checking the accuracy of a model using test data.
  3. Applying the model requires making changes after testing and using the finalized model for real-time projects.

Why Hire Machine Learning Engineers With Revelo?

HR managers and CEOs may have difficulty hiring the best machine learning engineers without a strong grasp of machine learning terminologies and concepts. But Revelo can help.

As Latin America's leading tech talent marketplace, we empower companies to find and hire world-class remote engineering talent who live in U.S. time zones, speak fluent English, and have been rigorously vetted for technical and soft skills. We also help you handle compliance, payroll, and benefits, giving you time to focus on growing your business.

Interested in learning more about how we can help you find qualified machine learning engineers to leverage ML models in your company? Contact us to start hiring top machine learning developers today.

‍

Developer Technologies

Our Talent is Experienced in these libraries, APIs, platforms, frameworks, and databases

Libraries

Frameworks

Facebook API | Instagram API | YouTube API | Spotify API | Apple Music API | Google API | Jira REST API | GitHub API | SoundCloud API

APIs

Amazon Web Services (AWS) | Google Cloud Platform (GCP) | Linux | Docker | Heroku | Firebase | Digital Ocean | Oracle | Kubernetes | Dapr | Azure | AWS Lambda | Redux

Platforms

Databases

MongoDB | PostgreSQL | MySQL | Redis | SQLite | MariaDB | Microsoft SQL Server

Frequently Asked Questions

Everything you need to know about hiring developers through Revelo

How much does it cost to hire developers through Revelo?
How quickly can I hire developers through Revelo?
Most companies receive their first shortlist of pre-vetted candidates within five business days. From there, the typical time-to-hire is 14 days from initial request to a developer starting work on your team. This timeline includes candidate review, interviews on your schedule, offer and acceptance, and onboarding setup.

Revelo can move faster for urgent needs. Because every developer in the network has already passed technical assessments, English proficiency evaluations, and soft skills screening before you see their profile, there is no waiting for sourcing or initial vetting. You are interviewing from a pool that is ready to start.
What is Revelo's vetting process for developers?
Every developer in Revelo's network passes a multi-stage vetting process before they are matched with any client. The process evaluates three dimensions: technical skills, English communication, and professional soft skills.

The technical assessment includes live coding challenges, system design evaluation, and a review of past projects and contributions relevant to the role. English proficiency is tested through structured conversation and writing exercises, with developers rated on fluency for real-time collaboration during US business hours. Soft skills screening covers communication style, reliability, time management, and experience working in distributed or remote teams.

Only the top 5% of applicants pass all three stages and enter the active talent pool. This means every candidate you interview through Revelo has already been validated for the skills, communication level, and work style that matter for your team.
What engagement models does Revelo offer for developers?
Revelo offers three engagement models for hiring developers from Latin America.

Full-time dedicated developers work exclusively for one company during overlapping US business hours, eight hours per day, under long-term employment agreements.

Contract engineering covers project-based work lasting three to twelve months, designed for product launches, migrations, feature sprints, or MVP development with defined scope.

Staff augmentation allows companies to build complete engineering squads of two to ten developers including a technical lead, while Revelo manages recruitment, onboarding, HR administration, and compliance.

Across all models, Revelo acts as the Employer of Record, handling payroll, tax compliance, benefits, and employment law obligations in the developer's country. Each model includes a 14-day replacement guarantee if the developer is not the right fit.
What happens after I hire developers through Revelo?
After hiring, Revelo serves as the Employer of Record and manages all ongoing employment administration. This includes monthly payroll processing in local currency, calculation and remittance of payroll taxes, and administration of mandatory benefits including health insurance and allowances as required under local labor law.

A dedicated account manager monitors the engagement, facilitates communication between your team and the developer, and addresses any performance or administrative issues. Revelo conducts quarterly performance check-ins with both the client and the developer to ensure alignment on goals and deliverables.

If the developer's performance does not meet expectations within the first 14 days, Revelo provides a replacement at no additional cost.

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