AI Engineer

Who we are 

Enhesa is the global compliance partner to the world’s largest businesses, bringing clarity to a regulatory and sustainability landscape that never stops changing.  

Our mission is to help organizations make informed decisions they can defend, wherever they operate, combining deep human expertise with AI efficiency, to confidently act across EHS, product, chemical, and corporate sustainability compliance.  

Businesses come to us needing help understanding what regulators expect. We’ve built our services around solving that problem and work with more than half of the fortune 500, as a trusted provider of intelligence. 

At Enhesa, our teams are guided by purpose, passion, inclusivity, and driving progress. We are united by a belief that positive change is everyone’s responsibility.  

If these qualities sound like you, Enhesa could be your next career move!

What we offer 

• A competitive salary package 
• Flexible home-working policy and work/life balance 
• A collaborative fast paced, driven environment 
• Accountability and pride for your projects 

For more information visit: www.enhesa.com 

Overview of the position

The Senior AI Engineer collaborates with other expert talents to develop, maintain, and assist in the deployment of natural language processing (NLP) AI products, from RAG systems to content generation and recommendation, to improve Enhesa’s customer experience. In addition to the required technical skills, the Senior AI Engineer has great organizational and communication skills and understands the challenges related to working with different languages.

The Senior AI Engineer is expected to keep up with the latest developments in the field of Artificial Intelligence engineering and be prepared to think creatively and apply novel techniques while solving business problems.

Main tasks and responsibilities

• Being comfortable with experimentation and showing a willingness to approach a problem in multiple ways via rapid prototyping.
• Identifying appropriate datasets and driving annotation for machine learning techniques.
• Developing and maintaining machine learning applications and products, together with relevant expert talents.
• Iteratively improving the developed AI systems and running evaluation experiments in collaboration with others, performing statistical analysis of results.
• Keeping an eye on the state-of-the-art of machine learning and GenAI solutions, emerging technologies, and developments in academia.
• Translating and communicating technical concepts and solutions to different stakeholders.