Agency Partners
I analyze live hiring data and tech job trends across Europe to give CTOs and Product Leaders a strategic edge. By tracking tens of thousands of open roles each week, I uncover which skills, roles, and locations are in highest demand — potential competitors, typical time to hire, talent pool sizes, and more to help you prioritize hiring, benchmark and stay competitive in a fast-moving market.
In recent weeks, the job market for Artificial Intelligence Machine Learning Engineers in the Netherlands has exhibited notable fluctuations. In week 9, there were 98 new job openings; however, this number has since decreased significantly, with only 8 openings recorded in week 14. Conversely, the closure of jobs shows a concerning trend, with a total of 129 jobs closed in week 11 alone, indicating a challenging recruitment environment. Comparatively, other roles in the Netherlands are witnessing a steadier pace of openings and closures, suggesting that the talent pool for Artificial Intelligence Machine Learning Engineer positions may be tighter than for other tech roles, necessitating refined recruitment strategies for CTOs and hiring managers in this competitive sector.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
|
Axelera AI | Netherlands | Semiconductors | 2021 | 16 |
|
TNO | Netherlands | Research | 1932 | 13 |
|
CIMSOLUTIONS | Netherlands | Information Technology & Services | 1992 | 8 |
|
Canonical | United Kingdom | Information Technology & Services | 2004 | 7 |
|
Sogeti | France | Information Technology & Services | 1967 | 5 |
|
Harnham | United Kingdom | Staffing & Recruiting | 2006 | 5 |
|
Booking.com | Netherlands | Information Technology & Services | 1996 | 5 |
|
ThePhoneLab | Netherlands | Telecommunications | 2015 | 5 |
|
Fellowmind | Netherlands | It Services | null | 5 |
|
Qualcomm | United States | Telecommunications | 1985 | 4 |
In the European job market for Artificial Intelligence and Machine Learning Engineers, the Netherlands presents a competitive landscape characterized by a notable ratio of job openings to the available talent pool. Specifically, while the Netherlands enjoys an impressive count of job openings, this is contrasted by a limited talent pool, indicating a challenging environment for tech leaders and recruiters. When compared to countries like Germany, France, and the United Kingdom, which also showcase high demand yet have a more favorable ratio of talent, it becomes evident that hiring AI and Machine Learning Engineers in the Netherlands is relatively more difficult. Consequently, CTOs and Engineering Managers should consider proactive recruitment strategies and possibly broaden their talent search to enhance their chances of finding the right candidates.
In the Netherlands, the seniority distribution for Artificial Intelligence Machine Learning Engineering jobs reveals that 48% of positions are classified as Mid-Senior level, followed by 24% at the Entry level and 13% at the Associate level. This distribution underscores the prominence of experienced professionals in the AI/ML sector, indicating a robust market for recruitment strategies targeting Mid-Senior level candidates.
The employment type distribution for engineering roles in the Netherlands reveals a clear preference for full-time positions, accounting for 94% of the job market. Contract roles make up 6%, while part-time opportunities represent 1% of the total engineering job landscape. This data underscores the competitive nature of the Artificial Intelligence and Machine Learning job market in the Netherlands, indicating a strong inclination towards securing full-time talent in these critical fields.
The time to hire distribution for Artificial Intelligence Machine Learning Engineer positions in the Netherlands showcases notable trends that are critical for hiring managers in the tech industry. A significant 236 positions were filled within a 25-day timeframe, indicating a relatively efficient recruitment process in this competitive job market. As candidates often remain in the pipeline for up to 30 days, with 394 counts reflecting this period, it highlights the ongoing demand for talent in this sector. The distribution reveals an increasing trend, as 87% of all hires occur within the first 40 days, aligning with emerging recruitment strategies for CTOs focused on expediting the hiring process. Understanding these hiring trends is crucial for tech leads and engineering managers to effectively position themselves and attract qualified candidates in the Artificial Intelligence Machine Learning domain.
In the Netherlands, the landscape for Artificial Intelligence Machine Learning Engineers reveals a concentrated presence in key urban centers. Amsterdam dominates the job market, accounting for 65% of the total openings, followed by Utrecht with 22% and Rotterdam at 12%. This concentration underscores Amsterdam's role as a pivotal hub for tech talent, affirming the capital's significance in the Artificial Intelligence Machine Learning job market in the Netherlands.
The Artificial Intelligence Machine Learning job market in the Netherlands highlights several prominent technologies driving demand for talent. Python emerges as the most sought-after language, with 13,742 mentions, followed closely by Machine Learning at 7,875. Data Analysis and Data Science also play critical roles, with frequencies of 3,843 and 2,810 respectively. Additionally, SQL (5,896), alongside Cloud technologies (1,171) and AWS (1,471), are essential components of the skill set for aspiring candidates. These technologies are visually represented in the accompanying chart, illustrating their significance in shaping hiring trends.
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