We Help You Hire a .Net AI Developer From South America
The process of hiring a Dot Net AI Developer from a nearshore company can often be confusing and time-consuming. You want a Dot Net AI developer with verified skills and experience who is smart, reliable, and hardworking.
Your organization can find the perfect fit for your development project using a custom AI matching algorithm. We ensure an excellent match for your team by combining data and personal interviews.
You can hire a Dot Net AI developer from our team who will contribute quality code immediately. We have refined our hiring process over the years, and many fast-growing startups trust it. Our Dot Net AI Software Developers are experts in their field, so hire yours with Hire Dot Net Developer and we’ll add one to your team.
US Working Hours
We have Brazilian developers who are able to work US hours so they can communicate and work well with your existing team.
Rates from LATAM
It has been a pleasure to bring together a wonderful group of software developers from Latin America who are eager to work with businesses in the United States.
One Simple Payment
You pay a flat monthly or hourly rate, and we take care of all employment taxes and employee benefits.
Vetted Developers Only
It is our guarantee that when you hire a developer with us, you are hiring a skilled professional who has passed our testing process.
Testimonials
Why Use Dot Net For AI Development?
.NET is a popular framework for developing AI applications because it provides a wide range of tools and libraries that can be used to build intelligent systems. The framework is designed to be flexible and scalable, making it ideal for building complex AI applications that require large amounts of data processing and analysis.
One of the key benefits of using .NET for AI development is that it provides a unified platform for building intelligent systems. This means that developers can use a single set of tools and libraries to build applications that run on multiple platforms, including Windows, Linux, and macOS.
Another advantage of using .NET for AI development is that it provides a high level of interoperability with other programming languages and frameworks. This makes it easy to integrate AI models into existing applications and systems.
.NET is a powerful framework for building AI applications that provides a wide range of tools and libraries for data processing, analysis, and modeling. It is flexible, scalable, and interoperable, making it an ideal choice for building complex intelligent systems.
ML.net is a powerful AI Machine Learning framework for .Net
ML.NET is a free, open-source, cross-platform machine learning framework made specifically for .NET developers. With ML.NET, you can develop and integrate custom machine learning models into your .NET applications, without needing prior machine learning experience. ML.NET is an extensible platform, with tooling in Visual Studio as well as a command-line interface for advanced users.
One of the key benefits of using ML.NET is that it provides a high level of interoperability with other popular machine learning frameworks such as TensorFlow and ONNX. This makes it easy to integrate ML.NET models into existing applications and systems.
Another advantage of using ML.NET is that it provides a wide range of tools and libraries for data processing, analysis, and modeling. This includes support for deep learning, natural language processing (NLP), and computer vision.
In summary, ML.NET is a powerful framework for building AI applications that provides a wide range of tools and libraries for data processing, analysis, and modeling. It is flexible, scalable, and interoperable, making it an ideal choice for building complex intelligent systems.
- Lots of Example AI Dot Net code available
- Use ML.net tools to process and load data.
- Fast for high volume calculations
- Most Popular AI Development Language
- Highly scalable
- Build ML models
- Implement MLOps
- Deploy models
Maria Silva
Dot Net AI Developer
8+ Years of Dot Net 4+ Years of AI Development.
Francisco de Oliveira
Dot Net AI Developer
11+ Years of Dot Net 7+ Years of Dot Net AI development.
Paulo de Souza
Dot Net AI Engineer
10+ Years of Dot Net 8+ Years of Dot Net AI development.
What does a Dot Net AI Developer do?
The definition of a .Net artificial intelligence developer is pretty straightforward: they develop software and applications for businesses that use artificial intelligence to complete business tasks. According to the data collected and analyzed, they program systems that will change as needed to suit the business’s needs. A good example is AI which recommends movies and Youtube channels based on what you previously watched or bought on your favorite streaming sites.
Data engineers, machine learning engineers, and data scientists often collaborate with AI developers. Those systems are also maintained by them to ensure smooth operation. An AI developer might be responsible for the following duties:
Using AI software, answer a variety of business challenges
Implementing, monitoring, and designing artificial intelligence systems
Describe AI’s potential and limitations to project managers and stakeholders
Develop an architecture for ingesting and transforming data
Incorporate AI technologies into your business as soon as possible
Educate teams on how to implement AI systems, an important customer service tool.
Proven Development Provider
As AI developers, we understand the importance of a reliable and high-performing partner. To meet each customer’s needs, we provide a premium service. Send us a message now to get started with your development team!
How to Hire a Senior Dot Net AI Developer with us?
Our Dot Net AI developers can be hired in three easy steps:
If you would like to send your requirements to us, please click the box below, fill out your requirements, click send, and send it by email.
Resumes are received and Dot Net AI developers are interviewed. Shortlist the professionals you want to interview once proposals start arriving.
During your requirement description, you will find out what the scope of your work is and what kind of Dot Net AI developer you require.
If you want a detailed response, include the following:
The scope of work includes website design, API development, and big data analytics.
The length of the project should be indicated in your job listing.
Industry experience requirements, like finance, should be mentioned here.
In the billing section, indicate whether hourly rates or monthly contracts are more suitable for you.
How much does it cost to Hire a Dot Net AI Developer?
The cost of a project is influenced by expert knowledge, experience, location, and market conditions.
As a Dot Net AI Developer acquires more experience, he or she will also be able to deliver better results, work faster, and have a greater understanding of the industry.
Those who gain experience may be able to charge higher rates for AI development.
The following hourly rates are available for Dot Net AI developers in South America:
Junior
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
Intermediate
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
Senior
Prices From- Works to U.S time zones
- No Recruitment Fees
- Vetted Skills & Experience
- Fulltime Working for you
- No Unreliable Freelancers
We’re supplying Dot Net AI Developers from South America!
The cost of developers may vary slightly depending on the requirements for skill and experience and availability.
It’s up to you to decide which one is the best one for your project based on the specifics.
What does Dot Net AI code look like?
Object-oriented programming is the core of .Net (the current iteration). Dot Net is all about classes and objects, along with their attributes and methods. A car, for example, is an object in real life. Besides attributes such as weight and color, the car also has methods such as braking and driving.
In our example code we will use ML.net a .Net AI framework referenced from the .Net code. The ML.net is used to create models and apply machine learning techniques in a scalable way.
Below we will give an example of how to use ML.NET to train a simple binary classification model:
using Microsoft.ML;
using Microsoft.ML.Data;
public class IrisData
{
[LoadColumn(0)] public float SepalLength;
[LoadColumn(1)] public float SepalWidth;
[LoadColumn(2)] public float PetalLength;
[LoadColumn(3)] public float PetalWidth;
[LoadColumn(4)] public string Label;
}
public class IrisPrediction
{
[ColumnName("PredictedLabel")]
public bool IsIrisSetosa;
}
public static void TrainModel()
{
var mlContext = new MLContext();
// Load training data
IDataView data = mlContext.Data.LoadFromTextFile<IrisData>("iris-data.txt", separatorChar: ',');
// Define data preparation pipeline
var pipeline = mlContext.Transforms.Conversion.MapValueToKey("Label")
.Append(mlContext.Transforms.Concatenate("Features", "SepalLength", "SepalWidth", "PetalLength", "PetalWidth"))
.Append(mlContext.Transforms.NormalizeMinMax("Features"))
.Append(mlContext.Transforms.Conversion.MapKeyToValue("Label"));
// Split data into training and testing sets
var (trainData, testData) = mlContext.Data.TrainTestSplit(data, testFraction: 0.2);
// Train the model
var estimator = pipeline.Append(mlContext.BinaryClassification.Trainers.SdcaLogisticRegression());
var model = estimator.Fit(trainData);
// Evaluate the model
var predictions = model.Transform(testData);
var metrics = mlContext.BinaryClassification.Evaluate(predictions);
Console.WriteLine($"Accuracy: {metrics.Accuracy}");
}This code uses the ML.NET library to train a binary classification model to predict whether an iris flower is a Setosa or not, based on its sepal length, sepal width, petal length, and petal width.
The code loads the training data from a text file, defines a data preparation pipeline that normalizes and concatenates the input features, splits the data into training and testing sets, trains the model using a logistic regression algorithm, and evaluates the accuracy of the model using the testing set.
This is just a simple example of how to use ML.NET, and the library supports a wide range of machine learning tasks and algorithms.
Interview Questions to ask your next .Net AI developer
Why do you like to program in .Net?
As a result, the candidate can share their Dot Net programming experience and thoughts on certain aspects of the language. Should code be written in an object-oriented or functional manner?
How do you ensure code quality?
Working on a Dot Net AI project requires quality control to ensure the end results are as expected. Check with the developer to see if the results are tested using any specific Dot Net development tools. Whenever engineers are working on Dot Net code, they must test for bugs and come up with ways to fix them.
What AI Algorithms have you used in the past?
You will gain insight into their thought processes when tackling AI problems by answering this question. When writing AI code, what are the most important things to keep in mind? How important is efficiency to them? How do they structure the problem? How good is their solution to the problem?
Do you like to write code as part of a team? or do you prefer to write code alone?
This question can be answered in any way, so there is no right or wrong answer. If you are looking to hire an engineer, you may need to hire one who is hardworking and independent. On the other hand, you might want someone who is good at working with others and not stubborn.
Tell us about a coding problem you solved?
Using this question, candidates will be able to demonstrate their approach to solving problems. By doing so, they will demonstrate their ability to work under pressure and solve problems.
This does not necessarily relate to Dot Net coding, though it might. In some cases, the problem can also be related to teamwork. The employee could explain how he or she reached a consensus with a colleague concerning a specific problem.
By dealing with conflicts, they will demonstrate that they are able to work with others.
Recent AI Development History
Below we cover a very brief history of recent AI developments since the 1980s.
Computers begin to talk
NLP (natural language processing) is a subfield of artificial intelligence that enables computers to understand human language. The first attempts to use computers to translate Russian and English were made in the early 1960s. As a result of these efforts, computers were thought of as being capable of understanding human languages. Most researchers, however, gave up on this idea by 1966 after failing to turn these ideas into reality.
With a steady increase in computational power and the adoption of new machine learning algorithms in the late 1980s, natural language processing experienced a leap in evolution. The new algorithms used statistical models rather than decision trees. There was a dramatic rise in statistical models for NLP during the 1990s.
Agents
Research in artificial intelligence shifted to something called intelligent agents in the early 1990s. Intelligent agents can provide news retrieval services, online shopping, and web browsing. Sometimes intelligent agents are referred to as agents or bots. Big Data programs have gradually evolved them into digital personal assistants and chatbots.
Machine Learning (ML)
Machine learning is one of the subdivisions of artificial intelligence used in the development of natural language processing. Although it has become a separate industry, answering phone calls and providing limited responses, it is still a foundation for AI. The field of artificial intelligence has become increasingly reliant on machine learning, as well as deep learning.
Rise of Chatbots
In response to spoken commands, digital virtual assistants complete tasks according to the instructions given.
As of 2011, Siri (of Apple) has become one of the most popular and successful digital assistants or chatbot. It may have started as a convenient way to get information about the weather, the latest news, and traffic reports, but advances in natural language processing (NLP) and access to massive amounts of data have made digital virtual assistants
Why we are a great choice to hire Dot Net AI Developer with?
With years of experience providing Nearshore Technology Solutions, we offer high quality developers at competitive prices. We offer scalable, high-performance solutions to our clients.
The expertise we possess in programming and project management allows us to accelerate or rescue development projects. With every project we develop, we strive to create lasting value.
Over a hundred startups and tech companies across the world have trusted us to match skilled developers with great teams.
With our .Net AI developers on your team, you can count on them to become dedicated team members, fully integrated into your operations.
To ensure the quality of our Dot Net AI developers, we conduct a thorough vetting process to determine their communication abilities, remote work readiness, and technical skills (both in Dot Net and AI development, as well as software development).
Better Prices
Usually, companies outsource to reduce costs. A software engineer hired from outside the United States will cost less. You will also be able to significantly reduce overall employment costs. No US or European employment taxes, benefits, or redundancy liabilities will apply.
Scaling Advantage
It is possible for any industry to gain a competitive advantage through quick expansion and downsizing. The benefits of outsourcing Brazilian developers to us are that your business can scale up or down as needed.
Experience in Development
Outsourcing software development gives you access to a company with extensive experience in helping businesses succeed. Therefore, you can be confident that your application will be delivered on time and on budget.
What do AI developers do?
AI developers are responsible for designing, developing, and implementing artificial intelligence systems and technologies for businesses. They work with stakeholders to identify business needs and opportunities, and then develop solutions that leverage machine learning, natural language processing, and other AI technologies to help businesses solve complex problems and gain competitive advantages.
In addition to technical skills, AI developers must have strong problem-solving, communication, and collaboration skills, as they often work with cross-functional teams and stakeholders to develop and deploy AI solutions. They must also stay up-to-date with the latest trends and developments in AI and machine learning to ensure that their solutions are effective and relevant to the needs of the business.
Overall, AI developers play a critical role in helping businesses unlock the value of AI technologies, from improving operational efficiency to enhancing customer experience and driving innovation.
To make better use of the data they already collect, many companies have embraced AI wholeheartedly over the past few years. AI is no longer an experimental technology reserved for select brands. Companies around the world have made it a core component of their operations.
- Improving the speed or consistency of service with AI
- Boosting efficiency through process automation AI
- Using customer insights and AI to inform decision-making
- Uncovering opportunities for new products and services
- HR using AI can read a job description in natural language
- Customized chatbots that can chat to customers and move them into your sales funnel.
The importance of code testing a Dot Net AI Developer
Code tests play a crucial role in hiring, as they help companies find the right candidates, along with other questions. In order for them to be effective, however, you need to customize each test so that it caters to your specific requirements and skills that the developer must possess. Therefore, it is imperative that you know exactly what you are looking for in a candidate. The test should include both Dot Net and knowledge of the AI framework you have selected and AI development in general, for example if you’re looking to hire a Dot Net AI developer.
We create the perfect coding assessment test that asks the right questions in the right format to pinpoint the candidate’s strengths and weaknesses. Besides measuring technical skills, we also assess a candidate’s soft skills at Hire Dot Net Developer.
How do you best manage the work of .Net AI Developers?
Normally, AI developers are supported by teams with a variety of skill sets that need to be managed effectively. A strong management structure is also essential for retaining technical talent.
Defining key results will help you meet your business objectives
A product owner, a development manager, and an architect can define milestones and outcomes to align on measurable success criteria. The leaders define the objective, then the team discusses, debates, and determines the key results together.
The best practice of defining OKRs on a regular basis is an important one. Defining and measuring OKRs too frequently can be costly, while infrequent measurement can lead to teams losing sight of them. I will give you two examples:
In order to improve application reliability, page response time, app availability, or error rates might be reduced.
In addition to automating tests and reducing build time, “improving deployment reliability” can also be achieved by reducing build time.
Selecting the right development methodology
Dot Net AI developers highly praise agile methodologies. Make a decision about the release schedule or sprint schedule.
In the typical one-week sprint, it’s almost impossible to finish big user stories within a week, but in the two-week sprint, vacations and unexpected problems are more likely to be addressed. Daily stand-up meetings help developers stay informed (and ask for help when necessary) about what everyone is working on.
You need to be able to communicate
A good engineering manager connects his or her team with the rest of the organization and with the customers. A Dot Net AI Developer needs to have a good understanding of the needs and constraints of the company’s customers, target audience, and the rest of the organization’s team.
The definition of your target audience’s needs helps you develop software that is both useful and profitable. It is imperative that Dot Net developers communicate directly with external teams and partners as needed while relaying relevant information to them.
We can help manage your remote team
Managing Dot Net AI development teams and implementing Agile methodologies are two of our services. In this view, people and exchanges are more important than procedures and devices, working software over comprehensive documentation, customer relationships over contract negotiations, and changing quickly over planning are more important than planning in advance.
The process of implementing Agile goes beyond adopting the Agile methodology. By taking the time to understand your business and the way you work, we help you choose the best Agile methodology. With the right working methodology, you can increase productivity, shorten the time-to-market, and eliminate defects.
How long does a .Net AI Developer job last?
The average Dot Net AI Developer in the US stays in the role between 1.2 and 2.8 years after they are hired, with larger companies tending to retain workers longer. In Brazil developers tend to spend a little longer in the same job at 1.8 and 3.6 years respectively. Traditionally, people spent their entire careers with the same company.
It’s not uncommon for experienced Dot Net AI developers to move from one job to another, seeking new opportunities and more money, as such longevity has decreased over time. In this market, where there is a low unemployment rate and a desperate need for mobile, cloud, and other vital technology skills, tech pros can migrate between jobs fairly easily (or even freelancing). A key component of our employee retention strategy is communication. We offer perks to keep top talent.
Frequently Asked Questions (FAQs)
Our services are trusted by hundreds of startups and tech companies worldwide, and we have matched hundreds of skilled developers to great development teams in the US, UK and Canada. Every AI developer in our network goes through a vetting process to verify their communication abilities, remote work readiness, and technical skills, both for depth in Dot Net and breadth across the greater programming domain.
The job description of a Dot Net AI Developer should include the following:
Developing, implementing, and managing software
New program testing and evaluation
Enhancing existing programs by identifying areas for improvement
Coding in an efficient manner
Analyzing operational feasibility
Establishing procedures for quality assurance
Implementing software tools, processes, and metrics
Upgrades and maintenance of existing systems
Assisting other developers, UX designers, and business analysts with their tasks
It’s not enough to just ship features; your software needs to help your business succeed. In order to better understand what you’re building, for whom, and why, we’ll begin our collaboration with a discovery process.
Our headquarters are in Sao Paulo, Brazil. We have clients from all over the world. We have successfully collaborated with companies in North America, Asia, the Middle East, and Europe. A good understanding of each client and excellent English communication skills help the process run smoothly.
We can work with you to scale the team down as needed and make sure you have the correct skills required for each project phase.
All Types! You can hire a Dot Net Developer on a full-time, part-time, or contract-to-hire basis at Hire Dot Net Developer. You can find a AI developer in a time zone that suits your needs thanks to our global network of skilled software engineers. Developers who work remotely for us are all mid- and senior-level professionals, ready to code right away.
