5 February 2024

By Mike  |  

Understanding the Role of AI Developers: A Deep Dive

By Mike H.

category : All

ON : 5 February 2024

Artificial Intelligence (AI) is reshaping the way we live and work. 

As per a report by Grand View Research, the global AI market size is expected to reach USD 733.7 billion by 2027, growing at a compound annual growth rate (CAGR) of 42.2% from 2020 to 2027. 

AI developers fuel this revolution—which is why companies hire AI developers in-house. 

They design and build intelligent systems that can learn from data, adapt to new inputs, and perform tasks that would usually require human supervision, creativity and intelligence.

Their work goes beyond coding algorithms. 

It’s more about understanding complex problems, designing effective solutions, and continuously learning and adapting over time. 

As Andrew Ng says:

“AI is the new electricity. Just as electricity transformed numerous industries roughly 100 years ago, AI is now poised to do the same.” 

In this article, we’ll go for a deep dive into AI developer duties.

6 Key Roles of An AI Developer

AI developers are tasked with various responsibilities that are necessary to the development and deployment of AI systems. Here are six core AI developer responsibilities:

  • Data Collection and Preprocessing

AI developers gather and preprocess data—which is a resource more precious than gold when it comes to AI. We use this data to train AI models.  

They might use various techniques to clean and normalize the data, removing any outliers or irrelevant information. 

They might also augment the dataset by creating modified versions of the information, such as data variation, to increase the diversity of the training data.

For instance, in a project involving image recognition, they might collect thousands of images and preprocess them to ensure they’re in a usable format for the AI model.

  • Algorithm Design and Training

AI developers design and train algorithms to learn from data—a very crucial concept where machine learning and deep learning come in. 

For example, they might design a neural network for a machine learning model and train it using a large dataset, adjusting parameters to improve its accuracy.

They might experiment with different types of neural networks, such as convolutional neural networks (CNNs) for image tasks or recurrent neural networks (RNNs) for sequential data. 

They also tune hyperparameters to optimize the model’s performance.

  • Model Implementation

AI developers implement AI models into real-world applications. These models are deployed in real-time, analyzing use cases. 

They might optimize the model for speed and memory usage and ensure it can handle a variety of input data.

For instance, an AI developer might integrate a trained machine learning model into a mobile app to provide personalized recommendations to users.

An AI developer might implement a fail-safe mechanism in a mobile app to handle cases when the AI model encounters an unfamiliar input.

  • Performance Tuning

AI developers monitor and fine-tune AI models to ensure ideal performance. This is done with feedback loops, constant upgrades and patch fixes. 

 They might use A/B testing or other evaluation techniques to measure the model’s performance and identify areas for improvement.

For example, if an AI model’s predictions start to drift over time, they might retrain the model with fresh data to improve its accuracy.

  • Documentation and Compliance

AI developers maintain detailed documentation of the AI development process, including the design of the AI model, the data preprocessing steps, and the performance evaluation results. 

They also ensure that all data handling practices comply with relevant data privacy regulations.

For instance, they might document the architecture of an AI model and the steps taken to anonymize data to comply with GDPR. Or they might implement secure data storage solutions and use encryption to protect sensitive data.

  • Collaboration and Communication

AI developers work closely with other team members and stakeholders, communicating complex AI concepts in a way that’s understandable to non-technical team members. 

They might use visualizations or simplified explanations to help non-technical team members understand the AI concepts.

They also collaborate with other developers, data scientists, and stakeholders to align the AI development with the overall project goals.

For example, they might explain the benefits and limitations of a proposed AI solution to a project manager.

The 5-Step Process For Hiring AI Developers

Hiring an AI developer is a critical step in capitalizing on artificial intelligence for your business. Here is a step-by-step process:

  • Identify Your Needs

Are you looking for someone to build machine learning models, or do you need an expert in natural language processing? 

The specific skills required will guide your hiring process.

  • Search For Candidates

Once you’ve identified your needs, you can start looking for candidates. 

  • Evaluate Applications

When evaluating candidates, consider their technical skills, experience with similar projects, and understanding of AI principles. 

Want to learn about the soft skills of AI developers? Explore our blog post by reading our extended discussion:The Importance of Soft Skills in AI Development Teams

  • Schedule Interviews

Interviewing AI developers can offer valuable insights into a candidate’s problem-solving skills and cultural fit. 

  • Consider Remote Hiring

Hiring AI developers online opens up a global talent pool, offering a wider range of expertise and flexibility. Visit Greelance that connects businesses with highly skilled and vetted freelancers from around the world. Check how to recruit the remote hiring by reading our insighful blog post “Remote Hiring: Best Practices for Virtual AI Developer Recruitment“.

Let’s Recap 

We hope that our blog was able to help you in exploring the role of AI professionals and the full scope of their workflow. To recap, here’s what we learned:

  • AI is the future, with an increasing demand for AI developers in all sectors.
  • There are six roles of an AI developer, including data collection, algorithm training, model deployment, tuning, documentation and collaboration. 
  • The process of hiring the right AI developer includes identifying needs, searching for candidates, evaluation, interviews and additional insight on remote hiring. 

Understanding AI developer contributions can help your business find the right one to skyrocket growth.

Frequently Asked Questions

Q1. What is the role of an AI developer?

AI developers design, build, and implement models for specific business issues, handling tasks such as data collection, preprocessing, algorithm design, training, implementation, performance tuning, and ensuring documentation and compliance.

Q2. How does AI learn?

AI merges large datasets with intelligent processing algorithms to learn from patterns. It uses logic-based techniques like machine learning for event interpretation, task automation, and actions with minimal human intervention.

Q3. How is deep learning connected with AI?

Deep learning utilizes deep neural networks for data processing and decision-making, mimicking human-like reasoning. This improves AI applications, automating tasks without direct human involvement.

Mike H.

Digital Marketing Head

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