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 the past twelve weeks, the job market for Artificial Intelligence Machine Learning Engineers in Lithuania has shown a fluctuating trend. Notably, there was a significant spike in job postings during week 20, reaching a peak of 9 new positions, while subsequent weeks saw a substantial downturn, with only 1 job posted in week 28. This fluctuation highlights a precarious balance between job openings and closures, with 4 jobs closed in week 18 and a total of 16 closures in both weeks 19 and 20. Compared to other roles within the Lithuanian tech landscape, the demand for Artificial Intelligence Machine Learning Engineers appears volatile, mirroring broader recruitment challenges faced across Europe's technology sector.
| Company name | Country | Industry | Founded | # Job openings | |
|---|---|---|---|---|---|
|
EPAM Systems | United States | Information Technology & Services | 1993 | 14 |
|
Canonical | United Kingdom | Information Technology & Services | 2004 | 6 |
|
Danske Bank | Denmark | Financial Services | 1871 | 6 |
|
Axelera AI | Netherlands | Semiconductors | 2021 | 5 |
|
Revolut | United Kingdom | Financial Services | 2015 | 3 |
|
Cognizant | United States | Information Technology & Services | 1994 | 3 |
|
Exacaster | Lithuania | Information Technology & Services | 2011 | 3 |
|
|
Cast AI | United States | Information Technology & Services | 2019 | 2 |
|
Unisys | United States | Information Technology & Services | 1816 | 2 |
|
Nord Security | Turkey | Computer & Network Security | 2012 | 2 |
The Artificial Intelligence Machine Learning job market in Lithuania is currently characterized by a competitive landscape, with job openings significantly outpacing the available talent pool. In comparison to neighboring countries, Lithuania has a jobs-to-talent ratio of 2.5, indicating a tighter hiring environment than Poland, which stands at 3.2, and Estonia, at 3.0. This underscores the burgeoning demand for Artificial Intelligence Machine Learning Engineers in Lithuania, as hiring trends suggest an increasing difficulty in sourcing qualified candidates. Additionally, compared to larger markets like Germany, which exhibits a ratio of 4.0, the urgency for recruitment strategies tailored for CTOs and tech leads in Lithuania's tech sector becomes evident. As the demand for Senior Artificial Intelligence Machine Learning Developers continues to rise, understanding these dynamics is crucial for effective talent acquisition in the region.
In Lithuania's burgeoning job market for Artificial Intelligence and Machine Learning Engineers, the seniority distribution reveals a significant emphasis on skilled professionals. Notably, 62% of positions are classified as Mid-Senior level, indicating a strong need for experienced individuals. Meanwhile, Entry level roles constitute 26%, while Associate positions account for 11%. This distribution highlights the growing demand for seasoned talent in the AI and Machine Learning landscape.
In Lithuania's engineering job market, the predominant employment type is full-time positions, comprising 96% of the available roles. Contract positions account for 4%, while part-time opportunities represent a smaller fraction at 2%. This distribution underscores the strong preference for stable, long-term employment within the technology sector, which is crucial for attracting and retaining Artificial Intelligence and Machine Learning Engineers.
The time to hire distribution for Artificial Intelligence job roles in Lithuania reveals significant insights into the recruitment landscape. Notably, 52 candidates were hired within a 30-day timeframe, indicating a robust availability of talent. However, as the hiring process extends to 45 days, the number decreases to 24, and further declines as the time reaches 100 days. This trend underscores the necessity for organizations, particularly CTOs and engineering managers, to adopt agile recruitment strategies to meet the impending demand for Artificial Intelligence and Machine Learning Engineers in Lithuania. Understanding these timeframes can aid hiring managers in optimizing their recruitment processes, ensuring they attract the best professionals amidst increasing competition in the tech sector.
In Lithuania's job market for Artificial Intelligence Machine Learning Engineers, Vilnius stands out as the leading city, accounting for 83% of the total job openings. Following Vilnius, Kaunas contributes to 9% of the market, while the broader indication for the country captures 5% of the available positions. This distribution underscores Vilnius as a pivotal hub for tech talent in this rapidly evolving field.
In the evolving landscape of the Artificial Intelligence Machine Learning job market in Lithuania, specific technologies emerge as pivotal for professionals in this field. Python leads with a notable frequency of 9008, reflecting its dominance in AI and Machine Learning projects. Following closely, SQL (3637) and Data Analysis (2107) are essential for data manipulation and evaluation. Java (1272), along with Cloud technologies (721) and AWS (998), are also critical for deploying machine learning models. The chart accompanying this paragraph illustrates these trends and emphasizes the importance of these technologies in shaping recruitment strategies for CTOs and tech leads in Lithuania.
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