Freelance AI Developers vs. Full-Time AI Engineers: What Businesses Should Consider

The era of artificial intelligence is not just approaching; it has already begun to reshape the fundamentals of today’s business landscape.

From AI-powered content creation tools to machine learning applications that forecast disruptions in the supply chain process, AI has transformed itself from a nice-to-have technology into a competitive edge.

However, as the use of AI technologies grows among companies, they encounter one important problem – the shortage of skilled AI experts on the market.

Attracting, screening and employing the talent capable of creating, training, and deploying AI solutions turns out to be not only a hard but an extremely costly process.

Many companies find themselves in a serious dilemma while assembling their technology team – whether to hire a dedicated AI specialist permanently, or utilize the emerging gig economy of AI experts.

There is no single solution that could be applied to the question of Freelance AI Developers versus Full-Time AI Engineers. The best approach is dependent upon the exact needs of your company when it comes to your particular project, budget, schedule, and technical objectives.

In this in-depth article, we are going to take a closer look at the AI staffing industry and examine the advantages and disadvantages of both types of employment models.

The AI Talent Market

But before moving on to think about the choice that you have to make with regard to the type of approach for hiring an AI developer, you must know a lot about the specific capabilities of such developers. When thinking about hiring a freelance AI developer, it is important to know their differences from a permanent one.

What is a Freelance AI Developer?

An independent machine learning developer, on the other hand, is a specialist who works alone in providing companies with his/her skills. Freelancers are people who work independently without being employees; they work just like independent companies.

They specialize in various fields of AI, such as natural language processing, computer vision, predictive analysis, and LLM fine-tuning.

In other words, when you employ a machine learning freelancer, you are employing him/her to assist you in solving certain problems or developing certain products. The typical activities that machine learning freelancers engage in include:

• Construction of a bespoke chatbot using the OpenAI API for customer service.

• Creation of a particular image recognition capability for an application.

• Checking and debugging of an already deployed but poorly performing machine learning pipeline.

• Development of a proof of concept (POC) or minimum viable product (MVP) in order to attract investors' funding.

The freelancing AI workers are mostly independent and design their services according to what the project needs. The versatility makes freelance AI developers a viable choice for firms with technical needs.

What is a Full-Time AI Engineer?

A full-time AI engineer is a permanent employee who is integrated into your company's organizational structure and works toward its long-term technical objectives. They are not hired to work on one project but hired to take care of all aspects of the lifecycle of your company’s AI infrastructure.

The work of full-time engineers revolves around the long-term governance of data, iterations, and the holistic integration of AI into your products. It typically entails:

• Creating and maintaining effective data pipelines.

• Watching for “data drift” and re-training your company’s machine learning models when needed.

• Collaborating closely with other departments such as marketing and sales departments and traditional software engineers to ensure that the AI is aligned with company objectives.

• Creating custom AI models from scratch using confidential company data.

The Case for Freelance AI Developers

The advantages that freelancers have for companies are absolutely astonishing, especially for young and middle-size companies. Companies hire freelance AI programmers to get specific knowledge without having a full-time job for them.

1. Affordable Costs & Versatility

One of the greatest benefits of employing a freelance AI programmer is saving money. In case of hiring freelancers, you pay solely for their work or hours that have been done.

You will be completely relieved of all the expenses related to permanent staff members such as healthcare insurance, vacation days, 401k matching, severance pay, etc.

Besides, this approach enables maximum scalability since AI development projects are usually done in stages. For example, you need a team of three programmers for a six-month period of time to complete the project, and afterwards just some minor maintenance works are required.

For companies working with freelance AI developers, this project-based approach can make it easier to manage development expenses.

2. Access to Niche, Specialized Skills

AI is not a unified science; it is an extremely large, unstructured accumulation of knowledge. While recommendation system and RAG applications development entail different problems from an engineering standpoint, experts in one domain may have transferable expertise that will make it easier for them to switch to another domain.

Freelancers typically take part in multiple projects, so they tend to be super-specialized. As such, by working with freelance engineers, you get a chance to create a “dream team” that would be customized for the particular stage of the project. So you could get the top 1% data architect to design your database in month one and a prompt engineer for LLM in month two.

This makes freelance AI developers particularly valuable when a business needs expertise in a specific AI technology or specialization.

3. Speed to Market

The timing of the market is essential in case you want your AI product to succeed. Hiring on a regular basis of an in-house AI engineer may potentially take from several months up to several years including sourcing, interviewing, negotiation, and going through the notice period.

Time taken in recruiting a freelance professional is less than recruiting a normal employee if there is clarity in project requirements and availability of technology.

They are experienced in rapid onboarding, fast integration into a new technology stack and doing their job as soon as possible. In case you have a tight schedule to integrate some AI functionality in your business, a freelancer machine learning specialist is likely to be your best choice.

Companies can also use freelance AI developers to accelerate product testing and implementation when time-to-market is a priority.

Drawbacks of Using Freelancers and the Solutions to Overcome Them

While hiring freelancers presents its own strengths, there are some weaknesses that come with this process. Data security issues and communication challenges are the two main weaknesses that companies will face in relation to the use of freelancers.

In addition to the above weaknesses, other issues related to availability, quality standards and knowledge transfer can be faced by firms in relation to the use of freelancers. Lack of availability and departure of a particular freelancer before the end of a project may cause some challenges to the business.

The Solution: Working with reputable platforms like Gigmint.AI can assist firms mitigate some of these weaknesses through the processes involved in developer screening and confidentiality agreements among others.Companies have to carry out their own due diligence to protect themselves in terms of intellectual property and management of data access.

When businesses employ freelance AI developers, they must set the milestone for projects right from the start.

The Case for Full-Time AI Engineers

While freelancers excel in speed and specialization, there are certain scenarios where building an in-house team is not just beneficial, but essential for the longevity of the business.

1. Deep Institutional Knowledge

The in-house AI engineer gets to know the ins and outs of your business like no outside contractor can. They get a grasp of the history behind your proprietary data sets, the long-term vision of your company's founders, and the quirks behind your legacy code bases.

And as a result, they create an AI system that is perfectly optimized to the needs of your organization. Not only do they create a model, but a model that is perfectly tailored to your specific users.

2. Ongoing Support and Maintenance

Another myth in the business sector about artificial intelligence is that AI is a ready-made technology that does not require any extra maintenance after its implementation.

Machine learning models need monitoring and maintenance since over time, they begin to face the problem of drift where their effectiveness and accuracy decline due to changes in real-world data.

This task of monitoring the performance of the model, identifying data drift, as well as organizing retraining of the deployed AI system can be performed by an in-house AI engineer.

3. Compatibility and Synergy of the Team

For the majority of projects, developing an AI product requires a team effort of various experts including data scientists, backend engineers, UI/UX designers, and product managers.

To state it briefly, a full-time employee is able to participate in ceremonies, brainstorms, and meetings held in the organization on a regular basis.

Potential Cons of Full-Time Hiring

One of the biggest drawbacks associated with employing an AI engineer on a full-time basis would be the massive investment that is required to do so. There is a serious shortage of skilled AI engineers, hence the salaries offered are really high.

Apart from salaries, companies will need to pay for costs associated with recruitment, onboarding, benefits, etc. Costs associated with recruitment may vary depending upon various factors.

There is always a possibility that in-house engineers will not have enough time to study the latest innovations in the field due to narrow specialization in a company's tech stack.

Key Factors to Consider When Making Your Choice

To solve the "Freelance AI Developers vs Full-Time AI Engineers" puzzle, there are four aspects that CTOs and business owners need to consider carefully.

1. The Scope and Length of the Project

The work itself dictates what kind of help should be provided.

Use Freelance When: Your project is short-term MVP creation, the integration of some external API (Claude or ChatGPT, for example), or when you just want some fast proof of concept.

When to Use Full-Time Position: Your entire product relies on AI (creating an automated driving car for instance), and the product/project development takes several years.

In case of short-term projects, freelancers can serve you with the necessary technical assistance without committing to a full-time job.

2. The Budget Considerations

It is obvious that the budgets for the development of AI technologies will look different for startups and enterprises. A bootstrapped startup may find it not so easy to invest a sum of more than $200,000 per year in the employment of a seasoned AI engineer. In such a case, spending $30,000 on developing the prototype in collaboration with a freelance AI developer may appear more economical.

On the contrary, a company may perceive the salary of the AI developer as its investment into intellectual property.

3. Data Security and Intellectual Property

To build artificial intelligence for a business, the developers should have access to their most sensitive information: data of customers, financial status of a company, algorithms, etc. In the case of dealing with highly regulated information like health information under HIPAA rules or personal information regulated by GDPR, businesses should take necessary precautions.

It is not enough to hire an employee of a company because there are some measures that should be taken even in the case of hiring an external contractor.If the data can be anonymized successfully or one can work as a freelancer in the enterprise level where the intellectual property is secured, freelancers will serve well.

Confidentiality and intellectual property agreements need to be sorted out when hiring freelance AI developers.

4. Technical Leader at Your Company Currently

Do you have a technical leader at your company right now who knows how to estimate the work of a freelancer? The freelancers need precise technical requirements and milestones. If your company doesn't have any technical leader at all, you need to hire a Lead AI Architect first in order to make this department.

Cost Breakdown: Freelance vs. Full-Time

In order to get a true picture of the financial consequences of both options, one must go beyond simply thinking about the hourly rate or the base salary. Below is a comparison of the actual costs involved when hiring AI professionals today.

These numbers below are just examples; these are not universal market rates. Rates of pay and freelancers vary depending on where you are located and your expertise.

Note: There exist significant differences in price depending on geographic region, skill set, and sub-specializations in AI. For instance, a professional who specializes in building generative AI architecture will cost much more than others in both freelance and full-time jobs.

In the end, full-time employment involves huge investment costs in return for future returns while freelance employment involves costs of operations and outputs.

Building an Agile AI Team

For many businesses in the modern world, the question of “Freelance vs. Full-Time” does not have to be an either/or choice, but a blend of the two.

Successful businesses can benefit from creating teams that use both full-timers and freelancers. For instance, a business could hire just one full-time Lead AI Architect or Director of Data Science. This person will take care of the company’s strategy and vision.

Underneath the one full-time employee, there will be a bunch of freelancers who will perform certain tasks. If you are required to optimize some neural network, you will take on an optimizer for one month. If you need a data scraper in one month, you will trade your optimizer for a Python data engineer.

If you own some SaaS company building an AI-enabled customer support software, you can have a full-time AI architect responsible for the technical strategy, model assessment, and infrastructure. The next step would be to use freelancers' help in developing chatbot integration, optimizing the system, and improving the performance of the model.

The combination of the two provides an opportunity for companies to enjoy the services of freelancers while having constant leadership and supervision.

How Gigmint.AI Helps Businesses Find AI Talent

In case you realize the potential in using freelancers and forming hybrid teams, then finding trustworthy specialists becomes another obstacle. There is an abundance of unvetted developers in the open internet and the process of finding suitable professionals takes too much time.

Gigmint.AI aims to connect businesses with AI professionals across different specializations, helping organizations identify talent for their specific technical and project requirements.

Gigmint.AI gives access to all of the following:

• Process of vetting: Give an account of the vetting procedures involved in assessing professionals in the online platform. Specify the processes involved.

• Matching algorithms: find exactly the specialist you need – from computer vision to LLM architecture – much faster than traditional recruiters can do.

• Secure engagement: Highlight the platform's available payment processes, confidentiality agreements and contractual provisions relating to intellectual property ownership.

Through the project named Gigmint.AI, businesses can get their hands on freelance AI programmers and connect with freelance AI developers who match their project requirements.

Final Thoughts

The choice between freelancers specializing in AI development and hiring full-time AI engineers is a significant strategic decision that may affect your budget and the rate of your company's development.

Full-time AI engineers ensure continuity, have knowledge about the organization, and continue working on AI systems. Freelance AI developers are flexible, specialize in particular tasks, and can change the rate of development depending on the needs of the project.

A hybrid solution is suitable for many companies and may combine the benefits mentioned above. It all depends on the project size, budget, security needs, and further plans of your company.

What do you need for your project, how much money do you have and what kind of technology does your company require? There is no universal solution – there is only the right one for you.

Are you ready to start your adventure with artificial intelligence? Find the best freelance AI developers from Gigmint.AI or contact our matching specialists now!

Frequently Asked Questions (FAQs)

Q: What is the price for hiring a freelance AI developer?

Answer: Employment of an independent AI developer entails costs which depend on the level of experience of the developer, range of specializations, the nature of the project, etc. The fee charged by developers for their work varies from $75 per hour up to $250 per hour or more, depending on the professional.

Q: How can I determine the level of qualification of an AI developer as a freelancer?

A: Do not make your decision only by analyzing their CVs. Study their GitHub pages, get acquainted with the examples of their case studies where they were developing machine learning projects before, and ask them to describe how they solved some problems like data drifts and API latency in the mentioned projects.

The usage of a reliable talent platform will make the process easier, but business organizations will still have to make interviews and check experience.

Q: Should startups hire freelance AI developers or full-time developers?

A: Freelance AI developers can be more useful for startups in the beginning of creating a product. They can develop MVPs, test ideas and introduce specific AI functions without making a financial investment for a constant position. But once the AI will become essential for the product or its further maintenance will be needed, it will be better to hire a full-time engineer or create a hybrid team.