Medior AI/ML Engineer

Role overview Build practical AI and machine learning solutions for client projects, taking features from prototypes into dependable services. You will own defined areas of delivery, combining Python data engineering with LLM-powered capabilities such as document processing, conversational assistants, and information retrieval.

Responsibilities - Develop Python data-processing services and ETL pipelines that prepare data for AI and machine learning workloads. - Implement LLM features such as retrieval-augmented generation, conversational interfaces, summarization, and API-based automation, including with AWS Bedrock. - Build and tune retrieval components, then check that they return useful, reliable results. - Validate system behavior with accuracy checks and regression tests before release. - Deploy and operate services on AWS using tools such as Lambda, S3, API Gateway, Step Functions, and, where appropriate, ECS or Fargate containers. - Contribute to architecture and technical scoping with guidance from senior engineers; follow code review, testing, documentation, and handover practices.

Requirements - Around 2–4 years building and shipping software with Python, ideally involving data or AI, or a portfolio demonstrating equivalent ability. - A relevant degree or a strong portfolio of real projects or open-source work. - Practical skills in cleaning, structuring, and storing data, and building APIs around it. - Experience connecting language models to real data and checking the accuracy of their answers. - Hands-on experience deploying and operating AWS services. - Professional spoken and written English, plus clear communication, independent execution, and early escalation of risks.

Nice to have - Client delivery or consulting experience, and experience moving prototypes into production. - AWS certification or interest in earning one; support for certification is available. - Familiarity with AI development frameworks, search-oriented databases, containers, orchestration, or infrastructure as code such as Terraform or CDK. - Hungarian or German language skills.

Benefits and work setup - Remote-first working arrangement, varied client projects, and ownership of meaningful live-system work. - Mentoring from senior engineers and support for AWS certification.