AI/ML Engineer

Egyéb juttatások
- Cafeteria
- Egészségbiztosítás
Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
Elvárt technológiák
- PYTHON AZURE SPARK
Elvárások
- Angol középfok
- 3-5 év tapasztalat
- Főiskola

Állás elmentve

A hirdetést eltávolítottuk a mentett állásai közül.

Architect and implement scalable AI/ML solutions on Azure or GCP
Design and build AI solutions for sales use cases
Automated RFP/RFI ingestion, classification, and response generation
Intelligent document understanding
Knowledge retrieval across product documentation, contracts, and past proposals
Sales assistant capabilities powered by LLMs
Develop and deploy LLM-based systems using prompt engineering, fine-tuning, and retrieval-augmented generation
Integrate ML and GenAI solutions with enterprise platforms
Drive the evolution of PoCs into robust MVPs
Implement MLOps practices including CI/CD, infrastructure-as-code, model versioning, and automated retraining and deployment pipelines
Provide technical guidance, code reviews, and architectural support to AI engineers
Mentoring and leading a distributed AI engineering team
Stay ahead of emerging AI trends, tools, and frameworks

Bachelor’s, Master’s or PhD in Computer Science, Engineering, Mathematics or related quantitative field
3+ years of experience in ML engineering or AI solution development with production deployments
Familiarity with Azure data & AI services or GCP equivalents
Strong experience with GenAI systems including LLMs, prompt engineering, fine-tuning, MCP and retrieval-augmented generation
Familiarity with agentic or multi-agent system concepts and architectures
Strong programming skills in Python
Self-starter mindset with passion for innovation and experimentation
Excellent communication skills in English

Hands-on experience with document AI, NLP, semantic search, or knowledge graph solutions
Experience with CI/CD pipelines for ML and infrastructure-as-code
Exposure to MLOps practices and tools
Hands-on Spark/Databricks expertise
Experience building PoCs and MVPs in AI/ML contexts
Familiarity with data engineering fundamentals
Demonstrated experience acting as a technical lead

Hybrid working with weekly 2 office days and flexible working hours
Financial benefits including cafeteria, referral reward and team or individual reward
Corporate health insurance package with nationwide coverage
Carefully designed career paths with training courses and projects
Language courses, tech talks and trainings
Lufthansa Group flight ticket discounts