msd
AI Engineer
At a Glance
- Location
- CZE - Central Bohemian - Prague (Five)
- Work Regime
- hybrid
- Employment
- Full time
- Experience
- 2+ years
- Posted
- 2026-03-19
Key Requirements
Required Skills
Domain Knowledge
- Engineering
Benefits & Perks
rral programme 5 weeks annual leave, 5 sick days, 15 days of cert
cases) Pension and health insurance contributions Internal reward system pl
Requirements
Bachelors or Masters in Artificial Intelligence, Machine Learning, or Computer Science is highly preferred, but qualifications in other quantitative disciplines are appreciated as well
2+ years of experience in AI Engineering
Strong communication and collaboration skills
Strong programming skills in Python
Must be analytical, detail-oriented, and able to balance multiple projects simultaneously
Familiarity with building scalable AI Solutions within a modern technology stack which includes cloud services, data pipelines, database, and other necessary tooling
Compensation & Benefits
Exciting work in a great team, global projects, international environment
Opportunity to learn and grow professionally within the company globally
Hybrid working model, flexible role pattern (e.g., even 80% full-time is possible in justified cases)
Pension and health insurance contributions
Internal reward system plus referral programme
5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements annually, 40 paid hours annually for volunteering activities, 12 weeks of parental contribution
Responsibilities
We are looking for an AI Engineer. Our team supports the business areas: research and development, manufacturing, supply chain, commercial and animal monitoring thought data science and AI delivery. This role allows you to work on impactful AI products and collaborate with AI engineers, data scientists, building a community that learns, challenges, and inspires each other. Our team is shaping the Data Science and AI strategy, serves as a DS and AI community facilitator and helps non-technical colleagues to mature their understanding of DS and AI.
Write efficient and maintainable code following best practices in software engineering.
Working with DevSecOps tools for deploying and versioning code.
Select appropriate retrieval techniques, language models, and generative AI methodologies.
Continuously iterate and refine retrieval augmented generation (RAG) methods and processes based on experimentation, analysis, and feedback.