AI Engineer (Python)
SMG Swiss Marketplace Group D.O.O. Beograd (Serbia)
- Design, build, and deploy AI solutions with a strong focus on LLM-powered systems
- Collaborate closely with data scientists, engineers, and product stakeholders to deliver production-ready AI features
Zahtevi

Potrebne kvalifikacije
Poželjne kvalifikacije
Welcome to SMG Swiss Marketplace Group
SMG Swiss Marketplace Group is Switzerland’s pioneering digital hub. Our multinational experts shape the future of our marketplaces to simplify people's lives and drive our customers' success.
A little bit about us to help ignite your imagination
Our exciting portfolio currently spans four business areas and includes Real Estate, Automotive, General Marketplaces, and Finance and Insurance.
At SMG Serbia , 160+ talents thrive in a fast-paced, collaborative environment, guided by our values: Better Together, Aim High, and Act Responsibly, shaping the future of digital marketplaces.
Job Description
As an AI Engineer at Swiss Marketplace Group's Real Estate Business Unit , you will contribute to the data hub for the leading real estate platforms in Switzerland, which includes homegate.ch and i mmoscout24.ch among others. You will be part of a cross-functional, agile data team with an open mindset and teammates who enjoy learning new skills and sharing theirs.
You will design, build, and deploy AI solutions with a strong focus on LLM-powered systems , including chatbots , information retrieval , and generative AI applications . You will work as part of the Data Science & Engineering team , collaborating closely with data scientists, engineers, and product stakeholders to deliver production-ready AI features.
About The Position
Design, build, and productionize scalable software solutions, with a primary focus on LLM-powered applications including chatbots, RAG systems, summarization, classification, and evaluation pipelines.
Own GenAI solutions end to end: from prototyping and architecture design to deployment, monitoring, scaling, and continuous improvement.
Integrate LLMs with internal data sources using retrieval techniques, embeddings, vector search, and search infrastructure.
Build reliable and maintainable ML / GenAI pipelines, including data ingestion, model orchestration, evaluation, deployment, observability, and alerting.
Apply LLMOps and MLOps best practices for scalability, reliability, cost efficiency, explainability, and governance.
Deploy and operate AI / ML systems in cloud environments such as AWS and GCP.
Build production-grade APIs, services, and integrations that expose ML / LLM capabilities to internal and customer-facing products.
Write, review, test, and debug high-quality Python code.
Own and improve existing ML / AI systems, including recommendation, prediction, fraud, and classification systems.
Collaborate with product, engineering, and business stakeholders to define objectives, success metrics, and production requirements.
Report to the Head of Data Engineering & Science.
Qualifications
5+ years of experience in software engineering with ML/AI background.
Strong Python skills, with a track record of writing clean, performant, testable, and maintainable code.
Proven experience deploying and operating ML, AI, or LLM-based systems in production.
Hands-on experience with LLMs, GenAI APIs, and frameworks such as OpenAI APIs, LangChain, LlamaIndex, Hugging Face, or similar.
Experience building RAG, chatbot, information retrieval, or AI assistant systems with end-to-end technical ownership.
Strong understanding of MLOps and/or LLMOps practices, including model deployment, evaluation, monitoring, retraining, versioning, and experiment tracking.
Experience with cloud infrastructure, especially AWS and/or GCP.
Experience building APIs, services, pipelines, and production integrations around ML / AI systems.
Comfortable working with CI/CD, containerization, infrastructure-as-code, observability, and production incident handling.
Familiarity with vector databases, embeddings, and search systems is a strong plus.
Comfortable working with large, heterogeneous datasets.
Ability to quickly understand new datasets and business problems.
Team-oriented, proactive, and comfortable with ambiguity.
Strong attention to detail and problem-solving mindset.
Fluency in English (written and spoken).
Additional Information
Why you'll love working here
- We value work-life balance and employee happiness. That’s why we grant you hybrid work environment, and 25 vacation days per year
- Private health insurance
- Lots of team activities and perks
- Free LinkedIn Learning & yearly budget for your personal development
- Profit Growth Scheme
- Company Phone (iPhone or Android)
- Cozy office space, with 80 parking spots
- Great equipment, competitive salary and a variety of fringe benefits like a gym membership and discounts at local stores
- International team and working environment of talented and fun people
- Stimulating work experience that will allow you to grow both professionally and personally
Apply now with your CV in English . Feel free to send us any additional documents you think we should read to understand that you are the perfect fit.
About Us
SMG Swiss Marketplace Group is a pioneering network of online marketplaces and a cutting-edge digital company that simplifies people’s lives with innovative products.
SMG Swiss Marketplace Group provides customers with the best tools to meet their life decision needs. The portfolio includes Real Estate (ImmoScout24, Homegate, Flatfox, CASASOFT, IAZI), Automotive (AutoScout24, MotoScout24), General Marketplaces (anibis.ch, tutti.ch, Ricardo) and Finance & Insurance (FinanceScout24, moneyland.ch).
Disclaimer
SMG Swiss Marketplace Group primarily engages with candidates directly. We do not accept unsolicited resumes or candidate profiles from recruitment agencies unless we have specifically requested their assistance for particular roles. Any submissions made without a prior request from our Talent Acquisition team will not be acknowledged or considered. We appreciate the understanding and cooperation of recruitment agencies in respecting this policy.
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