Get your SALARY indication as a machine learning (ML) or Artificial Intelligence (AI) engineer.
As a Machine Learning (ML) / AI Engineer, you will work daily with complex models, algorithms and data sets to develop valuable insights and intelligent systems. But do you actually know what you are worth in terms of salary and market value? What is a realistic hourly rate for your expertise in AI and machine learning? If you want to earn more and take your career to the next level, it is essential to know your market value well.
#ML #AI #DATA
Are you earning enough?
As a Machine Learning or AI Engineer, it is important to know your market value and therefore your hourly rate. Knowing what salary you are worth allows you to profile yourself and negotiate your rate and fringe benefits.
Many Machine Learning and AI engineers discover, after hearing their market value, that they are underpaid and that there is no transparency about construction.
Discover your market value with our tool and receive it on your 06 number within one business day. If you wish, we will remove your number afterwards.
YOUR SALARY UNDER THE MICROSCOPE.
Knowing your market value as a Machine Learning / AI Engineer allows you to better negotiate your salary and benefits. It helps you choose the right job, map out your career path and develop a strategy to achieve your professional goals.
We help you understand your market value so you know what hourly rate is realistic for an AI expert with your experience. This will help you earn more quickly and grow in your field in a more focused way. We guarantee this will help you accelerate your professional development and focus on the most important steps for your career.
So, want to know your worth and what salary fits a Machine Learning / AI Engineer of your level? Discover your market value and negotiate your salary smarter.
3 tips for a top salary.
The three most popular careers in Machine learning and Artificial Intelligence
Are you a Machine Learning Engineer, AI Engineer, MLOps Engineer or other specialist within AI and Machine Learning?
In a world where Artificial Intelligence, Machine Learning and MLOps are becoming increasingly important, the demand for specialized experts in the Netherlands has never been higher. The three most popular career paths within AI and ML are Machine Learning Engineering, AI Research and MLOps. But what do these roles actually entail?
Machine Learning Engineering
Machine Learning Engineers develop and implement models that recognize patterns, make predictions and improve themselves based on data. They ensure AI solutions are scalable, efficient and integrated into production environments.
AI Research
AI Researchers work on the theoretical and innovative side of AI, developing new algorithms and optimizing existing models. They contribute to cutting-edge research within deep learning, NLP and computer vision.
MLOps Engineering
MLOps Engineers build the infrastructure to deploy machine learning models reliably and scalably. They focus on CI/CD for ML, model monitoring, deployment, and automation to keep AI solutions in production efficiently.
Techniques & Tools: Where does your expertise lie?
Do you work with Python and frameworks such as TensorFlow or PyTorch? Are you proficient in distributed computing with Spark? Or do you specialize in Cloud AI solutions within AWS, Azure or GCP?
You might have experience with: Infrastructure-as-Code (IaC) such as Terraform and Bicep, Containerization with Docker and Kubernetes, MLOps & model monitoring with MLflow, Databricks or Kubeflow, API development with FastAPI or Flask, Model orchestration with Airflow and Prefect, CI/CD pipelines for automated model deployment.
Whatever your specialty, your unique combination of skills determines your market value as an AI and ML expert. Do you know what you’re really worth? 🚀
What hourly rate can you charge?
At Team Rockstars IT, we work with a 70/30 model, also known as a midlance construction. We believe that your expertise and performance should be fairly rewarded. That’s why 70% of the revenue goes directly to you! The higher your hourly rate, the greater your revenue-the more important it is to know exactly what your skills are worth.
This model combines the securities of permanent employment (you receive at least 55% of your own turnover each month, comparable to a market salary) with the freedoms of freelancing: you decide which projects you work on.
For Machine Learning Engineers, AI Engineers and MLOps specialists, this means a substantial increase in their hourly rate, often between 25% and 40%. And as your market value grows, you continue to make annual strides in your rate and career.
Why an ML and AI engineer needs to know what salary he/she can earn.
The salary of a Machine Learning Engineer, AI Engineer or MLOps specialist depends on several factors, including company size, industry, location and experience level. If you work at a large tech player with complex AI systems, you can usually expect a higher salary or rate than at smaller companies with less sophisticated AI applications.
In general, salaries for AI and ML experts are highly competitive because the demand for specialists in this field is huge. Companies increasingly rely on AI and data-driven decision-making, making experienced professionals indispensable.
As a Machine Learning Engineer or AI specialist, it is therefore crucial to understand the market value of your skills. This not only helps you in salary negotiations and choosing the right employer, but also in mapping out a career path that suits your expertise and ambitions.
our 3 pillars
Very simple. We’ll let you make a list. What kind of company would you like to work for? Where? With what techniques? What kind of culture? Based on your preferences, we will look for a suitable assignment. So you may also always say no to an assignment.
Talent Management
In our opinion, this does go hand-in-hand with a bit of guidance. Our Talent Managers make sure of that. Each Rockstar has its own Talent Manager. This talent manager is involved with you both professionally and personally. How is your skin and in your assignment? What is the situation at home? What is the state of our development goals? Are there any trainings or certifications that can contribute to this? Need a kick in the butt? Or just the occasional brake?
Your talent manager is involved in all of these things, making sure, among other things, that you properly monitor your balance and job happiness. On the other hand, the talent manager encourages your development.
Your fixed salary grows annually with your hourly rate. In addition to the fixed part, you will also earn a variable salary. This is the difference between the fixed revenue you get and your total 70% revenue.
We believe that doing business together works.
The working model we use is completely transparent and you will know at all times what hourly rate you are sitting at with one of our clients.
Here are three examples of IT Rockstars and their 70/30 model. We assume that all three of them work 43.5 weeks (1740 hours) for a client and 8 weeks not (5.5 weeks vacation, 1 week training, 1 week sick, 1 week no assignment).
Your 70% is your money. So you also decide how much you spend on a laptop, phone, training or car. So you can see that Suzanne has more salary left over because she chooses not to drive a leased car.
All the ducks are swimming in the water
….Falderal de riere Falderal de rare. Everyone knows the children’s song, of course. As soon as someone starts the first sentence, on autopilot, completely helpless, you follow the song as a chorus with the well-known- Fal de ral de ral de ra- piece. When you hear it you are overcome by a wonderful warm feeling, safety, trust and recognition. It may remind you of a family member or friend who used to always be there for you.
That feeling of ‘belonging somewhere’, the warm bath, safety and trust, that describes the feeling that everyone who works at Team Rockstars IT has.
No one should feel like the odd man out with us! People are central and that is what distinguishes us from our technical knowledge. Knowledge sharing is very important at Team Rockstars. We want to connect all existing IT expertise. That’s why we work in tribes!
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