AI Engineer (Portugal based - Remote model)

at  BoostIT

Boost IT is a Portuguese technology consultancy company, we are integrated into one of the most entrepreneurial groups in Portugal, with investment in more than 30 companies.
We want to be known for being the most dynamic, energetic and reliable company to operate in the market and, for that, we want to count on you.
If you’re passionate about technology and want to work on the most relevant technology projects, then this ad could be for you!
Boost IT. Doing IT. Better

Tasks

• Be comfortable withexperimentation; be willing to approach a problem in multiple ways via rapid prototyping.
• Identify appropriate datasets and drive annotation for machinelearning techniques.
• Develop (together with relevant expert talents) and maintain machine learningapplications and products.
• Iteratively (re-)train the developed models and run evaluation experiments in collaboration with others, performing statistical analysis of results.
• Keep an eye on state-of-the-art machine learning solutions, emerging technologies and developments in academia.
• Translate and communicate technical concepts and solutions to different stakeholders.

Requirements

• Expertise in the Scala programming languageis a mustExperience using Scala Play Framework.
• Advanced elastic search experience.
• Postgres database or other relationaldatabaseexperience.
• Experience in content apps.
• Experience in microservices.
• Knowledge ofa variety of AI techniques such as natural language processing, classification, clustering, optimization, deep neural networks with a good understanding of the mathematical underpinning and real-world advantages/drawbacks - preferred.
• Fluency in English is required, any additional language skills are an asset.
• Knowledge of data structures, semantic extraction, and text representationin an NLP context.
• Proficiency in Python (OOP) - preferred.
• Experience in using technologies such as Docker, Azure, GCP and AWS.
• Experience in creating APIs (RESTful, Asynchronous, etc.)
• Familiarity with the concepts and applications of LLMsa plus.

• Be comfortable withexperimentation; be willing to approach a problem in multiple ways via rapid prototyping.
• Identify appropriate datasets and drive annotation for machinelearning techniques.
• Develop (together with relevant expert talents) and maintain machine learningapplications and products.
• Iteratively (re-)train the developed models and run evaluation experiments in collaboration with others, performing statistical analysis of results.
• Keep an eye on state-of-the-art machine learning solutions, emerging technologies and developments in academia.
• Translate and communicate technical concepts and solutions to different stakeholders