Leading AI Solutions Specialist

7 days ago

Remote Warsaw Wrocław Białystok Kraków Gdańsk, Czech Republic beBeeDataScientist Full time 900,000 - 1,200,000
AI Leadership Role

We are seeking a highly skilled AI Tech Lead to drive innovation and excellence in our organization. As a leader in AI and Big Data, we are dedicated to helping clients deliver cutting-edge data projects.

The ideal candidate will have 5+ years of commercial experience in designing and implementing scalable AI solutions, including machine learning, predictive modeling, optimization, NLP, computer vision, and GenAI. They will also be proficient in developing ML algorithms from scratch to production deployment and possess strong programming skills in Python.

A successful AI Tech Lead will have the ability to lead the development, implementation, and validation of Machine Learning solutions, ensuring alignment with project objectives. They will also design AI solution architectures that meet complex business goals and drive innovation.

We are looking for a team player who can research, test, and select the best tools and technologies as well as AI solutions to meet the business requirements. The ideal candidate will understand client needs and translate business problems into data science problems.

In this role, you will work closely with cross-functional teams, including Data Engineering and Software Engineering, to strategize and oversee the building of AI applications. You will present findings and recommendations clearly and concisely to stakeholders and prioritize and control tasks within an Agile/Scrum framework, ensuring timely delivery.

  • Lead the development, implementation, and validation of Machine Learning solutions, ensuring alignment with project objectives.
  • Design AI solution architectures that meet complex business goals and drive innovation.
  • Research, test, and select the best tools and technologies as well as AI solutions to meet business requirements.
  • Understand client needs and translate business problems into data science problems.
  • Architect and oversee the implementation of data pipelines and workflows, setting standards for data quality and security.
  • Coordinate with Data Engineering and Software Engineering teams to strategize and oversee the building of AI applications.

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