AI/ML Engineer

We're looking for a talented AI/ML Engineer to join our newly formed Assetization Team in Prague. This team transforms proven AI use cases into reusable, scalable assets that deliver measurable business value. By collaborating with technical experts and business stakeholders, we ensure these solutions are practical, secure, and ready for global deployment.

Your impact at NN
Design, build, and refactor advanced AI/ML solutions—including Generative AI, Agentic systems, Large Language Models (LLMs), and traditional machine learning models—into robust, reusable, and scalable assets. Ensure these solutions are production-ready, deliver measurable business value, and can be applied across diverse use cases and domains.

Key Responsibilities

• Design and refactor AI/ML assets for reusability, scalability, and compliance with CoE and ART standards.

• Translate business and technical requirements into actionable user stories and maintain a prioritized backlog.

• Lead agile ceremonies including sprint planning, backlog refinement, and delivery coordination.

• Facilitate forward deployment by embedding with business units to validate and iterate on AI/ML assets in real-world contexts.

• Collaborate with ART and stakeholders to align on standards, share learnings, and prevent redundant development.

• Act as the primary point of contact for asset users and stakeholders across business units.

• Evangelize assetization best practices, manage risks and dependencies, and track KPIs and value delivered.

What we expect from you

• Degree in Computer Science, Engineering, or related field.

• 3–5+ years of experience in AI/ML engineering, including hands-on work with LLMs, GenAI, and traditional ML.

• Proficiency in Python and ML/AI frameworks (TensorFlow, PyTorch, Keras), with experience in agentic AI (LangChain, LangGraph), RAG, LLMOps/MLOps, and Databricks Mosaic AI.

• Experience deploying AI solutions in production environments (preferably Azure), with strong knowledge of CI/CD, Docker, Kubernetes, and RESTful APIs (FastAPI).

• Familiarity with AI architecture patterns, version control (Git), code review, and documentation best practices.

• Analytical and creative problem-solving mindset, with ability to work independently and manage multiple priorities.

• Strong communication and collaboration skills, with curiosity and drive for continuous learning and innovation.

• Advanced English proficiency required for working in an international environment.

Perks of joining NN

• We prefer a hybrid way of working. You can spend most of the week at home, but we usually have one day per week when we all meet in person. We'll help cover your home office costs

• We understand the importance of having a work-life balance, which is why we offer 5 weeks of vacation, 5 well-being days, additional paid time off for personal and family events, and 1 volunteering day to support our community.

• In addition to your base salary you will have a lump-sum meal allowance, up to CZK 20,000 in the Cafeteria per year, the possibility of arranging a MultiSport card, the possibility of contributing to supplementary pension insurance / supplementary pension savings, and a discount on life insurance.

• We believe that your professional and personal growth is crucial, which is why we provide you with tailor-made professional training.

• Your friends and acquaintances are a valuable source of talent for us, which is why we offer up to 60,000 CZK as a reward for recommending a suitable candidate.

• A business laptop and an iPhone with a paid O2 tariff and a data package are basic tools for your work.

What is the hiring process with us like

Once we review your application and English CV, Marek (Talent Acquisition Partner - RPO) will give you a short introductory call to discuss your previous experience and the open position. If this call goes well, we'd like to invite you to two interview rounds in total.
The first round will be an online meeting with Karel (Hiring Manager / AI & Automation Manager) and Marek (Talent Acquisition Partner – RPO). If the first interview goes well, we'll share a case study for you to complete within one week. After that, we'll schedule the second round—a technical interview with Karel and senior team members, where you'll present your case study and discuss it together with the team.