AI / ML Engineer

What we offer

• Possible hybrid model (2 days from the office weekly)

• Option to participate in trainings and conferences

• Staff travel benefits from day one

• Creative work tax deduction

• Multisport card

• Private health care

• Group insurance scheme

• Possible hybrid setting (minimum 1 day per week from the office)

• Possible permanent place in the office

• Possibility of taking part in trainings and certifications

• Great chance to meet your colleagues in other offices

• Annual events (i.e. St. Patrick’s Day 🍀)

• Regular social meetings 🍻

• Paid referral system

• New office building surrounded by great dinettes right in the city centre 🌆

• Contract of employment (permanent contract after trial period)

• or – – –

• B2B

• Other benefits:

Recruitment process

• Phone Call – get to know the Recruiter, and let us learn a bit about you.

• Technical assessment – a task sent via Github.

• Technical Interview – dive deeper with our Team to explore your expertise and approach. This stage will also include a live coding exercise.

• Final Interview – meeting with the Software Development Manager and Recruiter, combining technical questions and soft skills discussion.

• Offer – if we’re a match, we’ll present you with an offer and schedule your start day with us!

• Send us your application in English and let’s get started! Here’s what you can expect:

• During each of above steps we’ll be happy to answer any questions you may have. Apply today to discuss the role in more detail!

Competencies

• AI (Artificial Intelligence)

Requirements

• Proven experience in computer vision and NLP workloads.

• Deep understanding of knowledge mining techniques.

• Hands-on experience with generative AI models and familiarity with common use cases for Generative AI.

• Proficiency in Python and familiarity with software development best practices.

• Experience with MLOps/MLLops for maintaining machine learning lifecycle.

• Familiarity with Azure or AWS data science tooling.

• Familiarity with common Machine Learning techniques such as classification, regression, clustering, and deep learning.

• Infrastructure as Code (IaC) knowledge

• Familiarity with DevOps and Agile methodologies in a collaborative setting

• Doctorate degree (PhD) or equivalent research experience

• Bachelor’s or Master’s degree in computer science, Artificial Intelligence, Machine Learning, or related field.

• Proven track record of successfully implementing AI/ML projects.

• Nice to Have:

• Education and Experience: