5 дней назад
AI Engineer (Python)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Engineer (Python) (LLM/GenAI): Designing, building, and deploying production-ready AI solutions for real estate marketplaces with an accent on LLM-powered applications, RAG systems, APIs, and scalable ML pipelines. Focus on integrating LLMs with internal data, operating AI systems in AWS and GCP, and implementing LLMOps/MLOps practices for monitoring, evaluation, reliability, and cost efficiency.
Location: Hybrid, SMG office at Milutina Milankovića 1i, Belgrade, Serbia
Employment type: Full-time
Company
operates digital marketplaces across real estate, automotive, general marketplaces, and finance and insurance in Europe.
What you will do
- Design, build, and productionize scalable LLM-powered applications, including chatbots, RAG systems, summarization, classification, and evaluation pipelines.
- Own generative AI solutions from prototyping and architecture through deployment, monitoring, scaling, and continuous improvement.
- Integrate LLMs with internal data using retrieval techniques, embeddings, vector search, and search infrastructure.
- Build reliable ML and GenAI pipelines covering data ingestion, orchestration, evaluation, deployment, observability, and alerting.
- Deploy and operate AI/ML systems in AWS and GCP, including production-grade APIs, services, and integrations.
- Collaborate with data scientists, engineers, product stakeholders, and business teams to define objectives, metrics, and production requirements.
Requirements
- 5+ years of software engineering experience with an ML/AI background.
- Strong Python skills and experience writing clean, performant, testable, and maintainable code.
- Production experience deploying and operating ML, AI, or LLM-based systems.
- Hands-on experience with LLMs, GenAI APIs, and frameworks such as OpenAI APIs, LangChain, LlamaIndex, or Hugging Face.
- Experience with RAG, chatbot, information retrieval, or AI assistant systems, plus MLOps or LLMOps practices.
- Experience with AWS and/or GCP, APIs, CI/CD, containerization, infrastructure as code, observability, and production incident handling.
Nice to have
- Familiarity with vector databases, embeddings, and search systems.
- Experience with large, heterogeneous datasets and existing recommendation, prediction, fraud, or classification systems.
Culture & Benefits
- Hybrid work environment with a focus on work-life balance.
- 25 vacation days per year and private health insurance.
- Learning resources through LinkedIn Learning and an annual personal development budget.
- Profit Growth Scheme, company phone, gym membership, and local discounts.
- International, collaborative work environment with team activities and a well-equipped office.
Hiring process
- Apply with a CV in English.
- Additional documents may be submitted for consideration.
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