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In recent weeks, the Lithuanian job market has shown substantial fluctuations in the availability of Machine Learning Engineering roles. A notable spike in demand was observed during week 5, when 48 new positions were posted; however, this was followed by a decline, culminating in just one new posting by week 14. Comparatively, the broader European market significantly outpaced Lithuania, with weeks featuring thousands of new Machine Learning job postings. Despite this growing European demand, the closure of 55 positions in week 7 highlights a challenging recruitment landscape, contrasting with the relatively stable hiring trends for other tech roles in the region. For hiring managers, these insights emphasize the need to refine recruitment strategies to attract talent effectively in Lithuania's evolving Machine Learning job market.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
|
EPAM Systems | United States of America | It Services And It Consulting | 1993 | 13 |
|
Canonical | United Kingdom | Information Technology & Services | 2004 | 10 |
|
Revolut | United Kingdom | Financial Services | 2015 | 7 |
|
CAST AI | United States | Information Technology & Services | 2019 | 7 |
|
Nord Security | null | Computer And Network Security | 2012 | 7 |
|
Cognizant | United States | Information Technology & Services | 1994 | 5 |
|
Wix | Israel | Software Development | 2006 | 3 |
|
Danske Bank | Denmark | Financial Services | 1871 | 3 |
|
Baltic Assist | Lithuania | Outsourcing And Offshoring Consulting | 2015 | 2 |
|
Nortal | Estonia | It Services And It Consulting | null | 2 |
The job market for Machine Learning Engineers in Lithuania exhibits a competitive landscape, with an increasing number of job openings contrasted against a limited talent pool. Currently, Lithuania features a ratio of talent pool to job openings that suggests a challenging hiring environment, particularly when compared to countries like Poland and Germany, where the talent pool exceeds demand significantly. Conversely, countries like the Netherlands show a more favorable balance, with a healthier ratio that eases recruitment efforts. This disparity highlights the future demand for Machine Learning Engineers in Lithuania, making strategic recruitment approaches crucial for CTOs and hiring managers looking to fill these vital roles. Given the current trends in hiring Senior Machine Learning Developers across Europe, companies in Lithuania may need to adopt innovative recruitment strategies to attract the necessary talent.
In Lithuania's Machine Learning job market, a significant 65% of roles are classified as Mid-Senior level, reflecting a mature demand for experienced professionals. Entry level positions account for 26%, indicating a steady interest in nurturing new talent. Additionally, Associate roles comprise 14%, showcasing a growing attraction towards specialized skills in the field.
In Lithuania's engineering job market, the majority of roles are offered as Full-time positions, accounting for 97% of available jobs. Contract employment constitutes 4% of the market, while Internship opportunities make up about 1%. This distribution reflects a strong inclination towards stable, long-term employment, which is crucial for hiring managers seeking to attract and retain top talent in the competitive landscape of Machine Learning Engineers.
The time to hire for Machine Learning Engineer roles in Lithuania exhibits a notable distribution that hiring managers should consider when formulating their recruitment strategies. The majority of candidates, approximately 66, are hired within a span of 30 days, indicating a quick turnaround for the initial hiring process. However, the data reveals that the demand may extend beyond this timeframe, with significant counts observed up to 45 days and beyond, highlighting the potential challenges CTOs face in attracting top talent. As the job market for Machine Learning Engineers continues to evolve, understanding these hiring trends is crucial for driving effective recruitment strategies in Lithuania's tech sector.
The Machine Learning Engineers job market in Armenia reflects a dynamic landscape with distinct trends crucial for hiring managers and CTOs.
View ReportThe Machine Learning Engineers job market in Lithuania has shown significant fluctuations over the past three months, with a notable demand spike in week 5 leading to 48 new positions, contrasted by a decline to just one posting by week 14.
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The Machine Learning job market in Luxembourg has shown significant fluctuations over the past three months, with a total of 31 new roles posted in week 7, while 28 positions were closed shortly thereafter, indicating a highly dynamic and competitive recruitment landscape.
View ReportIn Lithuania, the distribution of Machine Learning Engineers job openings is prominently led by Vilnius, which accounts for 87% of the total job listings. Following Vilnius, Kaunas contributes with 8% of the opportunities, while an unspecified location represents 7%. This indicates that the majority of Machine Learning job market activity is concentrated in the capital, Vilnius, as depicted in the accompanying chart.
In the context of the Machine Learning job market in Lithuania, several key technologies emerge as pivotal for professionals in the field. Python, boasting a frequency of 18,881, stands out as the most frequently used programming language, essential for Machine Learning Engineer roles. Following closely are SQL and AI, with frequencies of 8,292 and 7,284 respectively, highlighting their significance in data manipulation and artificial intelligence applications. Additionally, the presence of Cloud technologies (1,684) and Java (1,980) further emphasizes the diverse skill set sought after in candidates. For a visual representation of these usage frequencies, please refer to the accompanying chart.
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