Upstaff

Hire AI Developer:
Unleashing the Power of AI

Upstaff is the best deep-vetting talent platform to match you with top AI developers remotely. Scale your engineering team with the push of button.
Upstaff
diceus
accenture
adidas
ciklum
proxet
valtech
diceus
accenture
adidas
ciklum
proxet
valtech
diceus
accenture
adidas
ciklum
proxet
valtech
Textures

5 Available Talents

All
Explore our full list of AI Developers
View All
Textures

Find AI Developers Your Way

Check 1-3 Days before you see the first candidates available to start within 1-2 weeks (vs 1-2 months average hiring period)
Check You get pre-screened, vetted, properly selected candidates matching your requirements
Check No long-term commitment is required
Check Pre-defined termination, no issues with employee termination
Find AI Developers Your Way
Check 1-3 Days before you see the first candidates available to start within 1-2 weeks (vs 1-2 months average hiring period)
Check You get pre-screened, vetted, properly selected candidates matching your requirements
Check No long-term commitment is required
Check Pre-defined termination, no issues with employee termination

Meet Our Team

We believe in fostering a transparent and inclusive environment where creativity thrives, empowering both clients and candidates to achieve their full potential.

Our Clients See Results

0%
See an increase in qualified candidates
0%
say that 50+ hours of engineering team time saved per developer on interviewing.
0%
Say their hiring process is now faster
Textures

Upstaff Model Comparison

Upstaff

Easier

You review profiles & meet only few pre-screened finalists to decide who will be join your team

Faster

Upstaff gives 1-3 Days before you see the first candidates available to start within 1-2 weeks

More Scalable

Together we identify project requirements and ideal candidate profile

Supervision

Engineer gets on-boarded. Upstaff team keeps supervising

Freelancers / Upwork

Item More Difficult
Item Less Reliable

In-house Recruitment

Item Slower
Item Less Flexible

Outsourcing Company

Item Less Scalable, Expensive
Item Professionalism & Quality

External Recruiter

Item Less Full Service
Item Without Supervision

Say their hiring process is now faster

E-commerce traffic management system

Company: NDA
Industry: E-commerce Location: Germany
802.1X

802.1X

Adobe CQ

Adobe CQ

AEM 6.4

AEM 6.4

Agile Project Management

Agile Project Management

Airtable

Airtable

About the client

The client is the key provider of smart web traffic management solutions, partnering with 52+ businesses across Europe — from enterprise companies to government applications.

Challenge

As the client has already worked with high volumes of data, the goal was to grow the web traffic, expand the network of partners, and transfer the project into an offline mode. It meant putting higher pressure on the network, which threatened to disrupt the entire system.

Solution

Our engineers discovered why servers crashed, fixed bugs that influenced web servers’ performance, and dealt with issues that interrupted the proper functioning of databases.

Key outcomes
  • Engineers updated the servers’ environment, infrastructure, and architecture of the database system, which let the system handle higher volumes of data
  • The traffic grew x3 in 4 months, which allowed the client to process over 5 million transactions daily

Landscape management solutions

Company: NDA
Industry: Landscape services Location: USA
Adobe Creative Suite

Adobe Creative Suite

Adobe CQ

Adobe CQ

Adobe After Effects

Adobe After Effects

Adobe Acrobat X

Adobe Acrobat X

Adobe Experience Manager (AEM)

Adobe Experience Manager (AEM)

Adobe indesign

Adobe indesign

About the client

The company has been serving facility professionals who manage various commercial properties since 1995. They offer a complex solution that covers site planning, mapping, and bonding, adding value by simplifying all ground management into one contract.

Challenge

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

Solution

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

Key outcomes

The client engaged our team when he needed to develop a new version of the landscaping operating software that’d manage the client’s contractors and subcontractors for groundworks. The challenge was to switch to the multitenant architecture in 2 months.

  • As our engineers achieved the goal in time, it gave space to move to the backlog tasks and develop new features
  • The team started preparing the system for switching to React, moving towards a yearly goal

French Luxury Brand

Company: NDA
Industry: Fashion Location: Paris
AbodeXD

AbodeXD

Active Directory

Active Directory

Active model serializer

Active model serializer

Active Server Pages (ASP)

Active Server Pages (ASP)

Adapt-Framework

Adapt-Framework

Ad-hoc testing

Ad-hoc testing

Actix Web

Actix Web

CSS

CSS

About the client

Being a world-class fashion house, our client offers chic clothing, bags, and jewelry, putting everyone who touches the brand in the lap of luxury. Headquartered in France, the company is among founding fathers of haute couture — one-of-a-kind, impeccable design.

Challenge

The company operates in 25 states with hundreds of stores and millions of customers worldwide. Enlarging the services, the client was lacking experienced PWA developers to refine its Magneto extensions on a regional website.

Solution

In just a week, developers kicked off the project and started working with Magento 2 and PWA Studio. The ultimate goal was to implement and develop custom modules and extensions. After six months of cooperation, the team presented shiny custom modules developed from scratch.

Key outcomes

As engineers worked on the project, the regional website performance along with the user engagement have increased.

  • The usability of the website was refined, which increased conversion rates by 10%
  • Overall user engagement grew by 35% while drop offs rate got lower
  • The brand got time to develop in other directions, continuing to grow its services
Introduction
Where to Find AI Developers
How to Assess AI Developer Skills
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Hire AI Developer - What to Expect
Quick Facts about AI
Where is AI used
Top 10 AI Related Tech:
Pros & Cons of AI
Top AI Instruments and Tools
Difference between Junior, Middle, Senior, and Expert AI Developers
Hard Skills of an AI Developer
Top 5 Cases AI Falls Short
Conclusion
Introduction
Where to Find AI Developers
How to Assess AI Developer Skills
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Hire AI Developer - What to Expect
Quick Facts about AI
Where is AI used
Top 10 AI Related Tech:
Pros & Cons of AI
Top AI Instruments and Tools
Difference between Junior, Middle, Senior, and Expert AI Developers
Hard Skills of an AI Developer
Top 5 Cases AI Falls Short
Conclusion
Introduction
Where to Find AI Developers
How to Assess AI Developer Skills
Common Mistakes to Avoid
Ensuring a Successful Collaboration
Case Studies
Hire AI Developer - What to Expect
Quick Facts about AI
Where is AI used
Top 10 AI Related Tech:
Pros & Cons of AI
Top AI Instruments and Tools
Difference between Junior, Middle, Senior, and Expert AI Developers
Hard Skills of an AI Developer
Top 5 Cases AI Falls Short
Conclusion

Introduction

Are you considering expanding your team with top-notch developers? Hiring a AI developer might be the game-changer your project needs. In this comprehensive guide, we explore the intricacies of finding and hiring skilled AI developers.

Where to Find AI Developers

Explore the various platforms available for hiring AI developers, from popular online platforms to specialized agencies. Learn about the benefits each option offers to streamline your hiring process.

How to Assess Node.js Developer Skills

Ensuring you have the right developer on board involves a thorough assessment. Delve into the details of technical interviews, evaluating real-world project experience, and choosing the developer whose skills align with your project requirements.

Common Mistakes to Avoid

Avoiding pitfalls in the hiring process is crucial for success. Learn about common mistakes, such as neglecting communication skills and ignoring cultural fit, to ensure a seamless collaboration.

Ensuring a Successful Collaboration

Setting the stage for success involves clear expectations and regular communication. Explore the strategies for ensuring a successful collaboration with your hired AI developer.

Case Studies

Read real-life case studies showcasing successful projects powered by AI. Dive into client testimonials and understand how AI developers have contributed to project success.

Hire Node.js Developer – What to Expect

Get insights into what to expect when hiring a AI developer, including timelines for project completion and continuous support post-deployment. Make informed decisions for a smooth development journey.

7 Facts about AI

AI, or Artificial Intelligence, is a fascinating realm of technology that reshapes our digital landscape:

  • Birth of AI (1956)

    AI emerges with the Dartmouth Conference, marking the beginning of research and development in artificial intelligence.

  • AI Winters (1970s-1980s)

    Periods of reduced funding and interest, known as AI winters, temporarily slow down progress in artificial intelligence.

  • Neural Networks Renaissance (2000s)

    The resurgence of neural networks breathes new life into AI, fostering breakthroughs in deep learning and pattern recognition.

  • Deep Blue Triumph (1997)

    IBM’s Deep Blue defeats chess champion Garry Kasparov, showcasing AI’s capability to outperform human experts in strategic games.

  • Machine Learning Dominance (2010s)

    Machine Learning takes center stage, empowering AI systems to learn from data and make predictions across diverse applications.

  • NLP Revolution (2018)

    The advent of advanced Natural Language Processing (NLP) techniques, like BERT, revolutionizes language understanding in AI applications.

  • Ethical Frontiers

    The ethical considerations surrounding AI, including issues of bias and responsible deployment, become critical aspects of AI development.

Where is AI used?

Revolutionizing Industries: AI is reshaping various sectors with its transformative capabilities.

Utilisation Case Description

Autonomous Vehicles

AI powers self-driving cars, improving road safety and optimizing transportation efficiency. The technology incorporates advanced sensors and real-time data processing to navigate and respond to dynamic road conditions.

Personalized Healthcare

AI is revolutionizing healthcare by leveraging patient data and genetic information to tailor personalized treatment plans. It enables precision medicine, optimizing therapeutic outcomes based on individual genetic profiles.

Fraud Detection Systems

AI-driven fraud detection systems analyze vast datasets in real-time, identifying unusual patterns and preventing fraudulent activities. These systems enhance security across financial transactions and online platforms.

Chatbot Technology

AI-driven chatbots provide instant and personalized customer support across various industries. They use natural language processing to understand user queries and deliver efficient responses, enhancing overall user experiences.

AI in Cybersecurity

AI plays a crucial role in cybersecurity, identifying and mitigating cyber threats in real-time. Machine learning algorithms analyze patterns, detect anomalies, and fortify digital landscapes against evolving security risks.

AI in Education

AI transforms education by adapting learning content to individual student needs. Personalized learning experiences are created, optimizing comprehension and engagement for students at various learning levels.

AI in Agriculture

AI optimizes agricultural practices by providing data-driven insights. Precision farming techniques and predictive analytics enhance crop yield, resource utilization, and overall farm management.

AI in Retail

AI revolutionizes the retail industry through personalized recommendations and market trend predictions. Enhanced customer engagement and targeted marketing strategies are facilitated by AI-driven analytics.

AI in Finance

AI powers predictive analytics and algorithmic trading in the financial sector. It analyzes market trends, predicts stock movements, and facilitates data-driven decision-making for traders and investors.

Top 10 AI Related Tech:

  1. Quantum Computing: The Mind-Bending Machine

    Quantum Computing is the eccentric genius of the tech world, bending reality itself. It dances with qubits, performing computations that leave traditional bits scratching their binary heads.

  2. Neural Networks: The Brainy Babble

    Neural Networks are the divas of AI, mimicking the brain’s neural connections. They learn from data, creating a cacophony of weights and biases to decode patterns and make predictions.

  3. Python: The Snake Charmer Language

    Python is the enchanting language that slithers through AI development. Its syntax is a dance, gracefully coiling around algorithms and data structures, making it the snake charmer’s choice.

  4. TensorFlow: The Ballet of Tensors

    TensorFlow orchestrates a ballet with tensors, pirouetting through neural networks. Its choreography of computations flows seamlessly, transforming data into a mesmerizing performance.

  5. NLP Libraries: The Language Wizards

    NLP Libraries, like NLTK and SpaCy, are the wizards of language manipulation. They parse sentences, conjuring semantic meaning and allowing machines to speak the human tongue.

  6. Reinforcement Learning: The Gamified Guru

    Reinforcement Learning is the gamified guru, teaching AI through rewards and punishments. It’s the mentor behind machines mastering complex games, turning pixels into profound strategies.

  7. Edge Computing: The Close-Up Conjuring

    Edge Computing is the close-up magician of AI, performing feats right where the action happens. It brings intelligence to the edge, minimizing the latency between computation and result.

  8. GANs: The Artistic Illusionists

    GANs are the artistic illusionists, crafting images that blur the line between real and fake. They paint with pixels, creating visual masterpieces that challenge human perception.

  9. Robotics Frameworks: The Metal Symphony

    Robotics Frameworks conduct a symphony of metal and code, choreographing the movements of AI-driven robots. They turn nuts and bolts into a harmonious dance of automation.

  10. AutoML: The Lazy Genius

    AutoML is the lazy genius, automating the model-building process. It’s the wizardry that allows even the laziest developers to conjure powerful AI models without breaking a sweat.

Pros & Cons of AI

Overview: Artificial Intelligence, a technological marvel, brings both promise and challenges. It’s a double-edged sword, cutting through tasks with precision but leaving concerns in its wake.

Pros:

  • AI Enhances Efficiency: With its lightning-fast processing, AI turbocharges tasks, boosting productivity and streamlining operations.
  • Unmatched Precision: AI’s ability to analyze vast datasets with pinpoint accuracy surpasses human capabilities, ensuring precision in decision-making.
  • Innovative Solutions: AI fuels innovation, offering solutions to complex problems through advanced algorithms and creative problem-solving.
  • 24/7 Availability: Machines don’t sleep. AI systems tirelessly operate around the clock, providing continuous services and support.
  • Automation Revolution: AI automates mundane tasks, freeing up human resources for more strategic and creative endeavors.

Cons:

  • Ethical Dilemmas: AI introduces ethical concerns, especially in decision-making processes, raising questions about fairness and bias.
  • Lack of Creativity: Despite its prowess, AI struggles with creativity and the emotional nuances inherent in certain human-centric tasks.
  • Job Displacement: The automation revolution comes at a cost, potentially displacing jobs and necessitating reskilling in the workforce.
  • Security Risks: AI systems, if not secured properly, pose significant risks, including data breaches and vulnerability to cyber-attacks.
  • Overreliance Concerns: Excessive dependence on AI may lead to overreliance, reducing human skills and hindering problem-solving abilities.

Top AI Instruments and Tools

  • TensorFlow

    Overview: TensorFlow, developed by the Google Brain team, is a robust open-source machine learning library. It’s a powerhouse for building and deploying machine learning models.

    History: Released in 2015, TensorFlow quickly gained popularity and has become a standard in the AI community.

    Usage: Widely used for image recognition, natural language processing, and various machine learning applications.

  • PyTorch

    Overview: PyTorch is a dynamic deep learning framework known for its flexibility. It’s widely embraced in academia and industry for its ease of use.

    History: Developed by Facebook, PyTorch gained traction for its user-friendly interface.

    Usage: Popular in natural language processing, computer vision, and research-oriented projects.

  • Scikit-learn

    Overview: Scikit-learn is a simple yet powerful machine learning library. It provides tools for data mining and data analysis.

    History: Released in 2007, it has been a staple for machine learning enthusiasts and professionals.

    Usage: Commonly used for classification, regression, clustering, and dimensionality reduction tasks.

  • Keras

    Overview: Keras, now integrated with TensorFlow, is a high-level neural networks API. It simplifies the process of building deep learning models.

    History: Originally developed as an independent library, Keras became synonymous with ease of use in deep learning.

    Usage: Ideal for rapid prototyping and building neural networks with minimal complexity.

  • NVIDIA CUDA

    Overview: NVIDIA CUDA is a parallel computing platform enabling GPU acceleration. It’s crucial for high-performance AI applications.

    History: Introduced by NVIDIA in 2006, CUDA has transformed how AI tasks leverage GPU capabilities.

    Usage: Accelerates computations for deep learning models, enhancing processing speed.

  • Jupyter Notebooks

    Overview: Jupyter Notebooks provide an interactive environment for data science and AI development. They allow users to create and share documents containing live code, equations, visualizations, and narrative text.

    History: Originally part of the IPython project, Jupyter has evolved as a key tool in data science and AI.

    Usage: Ideal for collaborative coding, data exploration, and visualization in AI projects.

  • IBM Watson

    Overview: IBM Watson is an AI platform that offers a suite of tools and services for building and deploying AI solutions.

    History: Introduced by IBM in 2010, Watson gained fame for winning Jeopardy! against human champions.

    Usage: Utilized in various industries for natural language processing, image recognition, and chatbot development.

  • OpenCV

    Overview: OpenCV (Open Source Computer Vision Library) is a powerful open-source computer vision library for image and video processing.

    History: Originally developed by Intel, OpenCV has a rich history and continuous community contributions.

    Usage: Essential for tasks like facial recognition, object detection, and image manipulation in AI projects.

  • Azure Machine Learning

    Overview: Azure Machine Learning is a cloud-based service from Microsoft that facilitates the end-to-end machine learning lifecycle.

    History: Launched by Microsoft in 2019, Azure ML has become a go-to platform for developing, training, and deploying machine learning models.

    Usage: Integrated with Azure services, it supports various machine learning tasks in diverse industries.

  • Pandas

    Overview: Pandas is a fast, powerful, and flexible open-source data manipulation tool built on top of Python.

    History: First released in 2008 by Wes McKinney, Pandas has become a standard library for data

Difference between Junior, Middle, Senior, and Expert AI Developer

When hiring for AI development roles, understanding the distinctions between Junior, Middle, Senior, and Expert/Team Lead positions is crucial. Below is a comprehensive comparison of these roles.

Aspect Junior Middle Senior Expert/Team Lead
Years of Experience 0-2 years 2-5 years 5-8 years 8+ years
Task Complexity Handles basic tasks under supervision Tackles moderate complexity tasks independently Manages complex projects and mentors others Leads and strategizes complex AI initiatives
Average Salary (USD/year) $60,000 – $80,000 $80,000 – $100,000 $100,000 – $120,000 $120,000+
Performance Learning and adapting to tasks Consistent delivery of quality work High-level performance, innovative solutions Exemplary performance, strategic leadership
Quality-wise Produces functional solutions Produces efficient and effective solutions Ensures high-quality, scalable solutions Defines and maintains top-tier quality standards
Team Collaboration Collaborates within a team Collaborates across teams, mentors juniors Leads and collaborates at a departmental level Leads cross-functional teams, influences strategy
Example Tasks
  • Implementing predefined algorithms
  • Assisting in data preprocessing
  • Code debugging and optimization
  • Developing machine learning models
  • Participating in project planning
  • Optimizing existing algorithms
  • Leading end-to-end AI projects
  • Providing technical guidance
  • Researching and adopting new technologies
  • Defining AI strategy and architecture
  • Mentoring senior team members
  • Overseeing multiple complex projects

Hard Skills of an AI Developer

AI developers require a mix of technical expertise to excel in their roles. Here are the hard skills categorized by experience level:

Junior

  • Python programming
  • Basic understanding of machine learning concepts
  • Data preprocessing and cleaning
  • Algorithm implementation
  • Knowledge of popular AI frameworks (e.g., TensorFlow, PyTorch)

Middle

  • Advanced machine learning model development
  • Deep learning proficiency
  • Natural Language Processing (NLP)
  • Computer Vision skills
  • Collaborative coding using Git
  • Cloud computing platforms (e.g., AWS, Azure)
  • Big data processing tools (e.g., Apache Spark)
  • Experience with containerization (e.g., Docker)

Senior

  • Leadership in AI project management
  • Advanced AI research capabilities
  • Optimization of complex algorithms
  • Expertise in distributed computing
  • Deployment and scaling of AI models
  • Cybersecurity in AI applications
  • Advanced knowledge of AI ethics and regulations
  • Custom model development
  • Performance tuning

Expert/Team Lead

  • Strategic AI planning and architecture
  • High-level decision-making in AI projects
  • Mentoring and team leadership
  • In-depth understanding of AI hardware
  • Integration of AI with business strategies
  • AI patenting and intellectual property
  • Cross-disciplinary collaboration
  • AI-driven innovation
  • Creating and maintaining AI coding standards
  • Implementing AI in edge computing
  • Quantum computing knowledge

Back-End

  • Server-side programming languages (e.g., Java, C++)
  • API development and integration
  • Database management and optimization
  • Scalable system design
  • Understanding of RESTful architecture
  • Security protocols implementation
  • Knowledge of microservices architecture
  • Container orchestration (e.g., Kubernetes)

Full-Stack

  • Front-end development (HTML, CSS, JavaScript)
  • Responsive web design
  • UI/UX principles
  • Integration of AI into web applications
  • Version control (e.g., Git)
  • Knowledge of web frameworks (e.g., Django, Flask)
  • Continuous integration and deployment
  • Collaboration with UI/UX designers
  • Mobile application development
  • Front-end testing frameworks

Soft Skills of an AI Developer

Beyond technical expertise, successful AI developers possess essential soft skills crucial for effective collaboration and problem-solving:

Soft Skills Overview:

  • Effective communication
  • Adaptability to evolving technologies
  • Problem-solving mindset
  • Attention to detail
  • Team collaboration and leadership
  • Critical thinking
  • Time management
  • Continuous learning orientation
  • Client-focused approach
  • Emotional intelligence

Top 5 Cases AI Falls Short

Data Quality Issues

AI struggles when faced with poor-quality data, leading to inaccurate predictions and unreliable outcomes.

Unpredictable External Factors

AI may falter when unforeseen external factors, such as sudden changes in market conditions or unexpected events, impact the underlying assumptions of the models.

Complex Human Emotions and Social Context

AI encounters challenges in understanding and responding appropriately to complex human emotions and intricate social contexts, limiting its effectiveness in certain applications.

Lack of Ethical and Moral Understanding

AI lacks inherent ethical and moral understanding, making it prone to biases and potentially contributing to decisions that may be deemed ethically questionable by human standards.

Security and Adversarial Attacks

AI systems are susceptible to security breaches and adversarial attacks, where intentional manipulations can deceive the models and compromise their functionality.

Conclusion

In conclusion, hiring AI developer is a strategic move for any development project. By understanding the key skills, avoiding common mistakes, and fostering a successful collaboration, you set the stage for a seamless and efficient development journey.

FAQs about Hiring AI Developers

How to choose the right developer? Arrow

Choosing the right AI developer involves assessing skills, experience, and cultural fit. Look for a developer whose expertise aligns with your project requirements.

What is the average cost of hiring? Arrow

The cost of hiring a AI developer varies based on experience and location. On average, rates range from $35 to $50 per hour, with additional costs for specialized skills.

Ensuring code security Arrow

AI developers should prioritize code security. Ensure your developer follows best practices, conducts regular security audits, and stays updated on the latest security trends.

Handling scalability issues Arrow

Scalability is crucial for successful projects. Hire a developer with experience in building scalable applications and addressing potential bottlenecks in AI.

Resolving conflicts in development Arrow

Conflicts may arise during the development process. Effective communication and a collaborative approach are key to resolving conflicts and maintaining a positive working relationship.

How to hire AI developers? Arrow

If recruiting services and job boards are not your 1st option, you may want to consider a client-oriented service like Upstaff to find & hire AI developers. Upstaff has a network of vetted and tested AI engineers. Here you can hire web developers for a few simple coding tasks with AI.

Reviews
Henry Akwerigbe
Henry Akwerigbe
This is a super team to work with. Through Upstaff, I have had multiple projects to work on. Work culture has been awesome, teammates have been super nice and collaborative, with a very professional management. There's always a project for you if you're into tech such Front-end, Back-end, Mobile Development, Fullstack, Data Analytics, QA, Machine Learning / AI, Web3, Gaming and lots more. It gets even better because many projects even allow full remote from anywhere! Nice job to the Upstaff Team 🙌🏽.
Vitalii Stalynskyi
Vitalii Stalynskyi
I have been working with Upstaff for over a year on a project related to landscape design and management of contractors in land design projects. During the project, we have done a lot of work on migrating the project to a multitenant architecture and are currently working on new features from the backlog. When we started this project, the hiring processes were organized well. Everything went smoothly, and we were able to start working quickly. Payments always come on time, and there is always support from managers. All issues are resolved quickly. Overall, I am very happy with my experience working with Upstaff, and I recommend them to anyone looking for a new project. They are a reliable company that provides great projects and conditions. I highly recommend them to anyone looking for a partner for their next project.
Владислав «Sheepbar» Баранов
Владислав «Sheepbar» Баранов
We've been with Upstaff for over 2 years, finding great long-term PHP and Android projects for our available developers. The support is constant, and payments are always on time. Upstaff's efficient processes have made our experience satisfying and their reliable assistance has been invaluable.
Roman Masniuk
Roman Masniuk
I worked with Upstaff engineers for over 2 years, and my experience with them was great. We deployed several individual contributors to clients' implementations and put up two teams of upstaff engineers. Managers' understanding of tech and engineering is head and shoulders above other agencies. They have a solid selection of engineers, each time presented strong candidates. They were able to address our needs and resolve things very fast. Managers and devs were responsive and proactive. Great experience!
Yanina Antipova
Yanina Antipova
Хочу виразити велику подяку за таку швидку роботу по підбору двох розробників. Та ще й у такий короткий термін-2 дні. Це мене здивувало, адже ми шукали вже цілий місяць. І знайдені кандидати нам не підходили Це щось неймовірне. Доречі, ці кандидати працюють у нас і зараз. Та надать приклад іншим працівникам. Гарного дня!)
Наталья Кравцова
Наталья Кравцова
I discovered an exciting and well-paying project on Upstaff, and I couldn't be happier with my experience. Upstaff's platform is a gem for freelancers like me. It not only connects you with intriguing projects but also ensures fair compensation and a seamless work environment. If you're a programmer seeking quality opportunities, I highly recommend Upstaff.
Volodymyr
Volodymyr
Leaving a review to express how delighted I am to have found such a great side gig here. The project is intriguing, and I'm really enjoying the team dynamics. I'm also quite satisfied with the compensation aspect. It's crucial to feel valued for the work you put in. Overall, I'm grateful for the opportunity to contribute to this project and share my expertise. I'm thrilled to give a shoutout and recommendation to anyone seeking an engaging and rewarding work opportunity.

Boost Your Product Development with Upstaff.

Work with the largest network of software engineers and independent contractors to scale your project.
Boost Your Product Development with Upstaff.