AI Engineer

ppArtificialyis an AI company based in Switzerland, with offices in Lugano and Zurich. We design and deliver AI solutions that are impactful, transparent, and tailored to real-world industry needs. /p pFounded in 2020 by pioneers with over 40 years of combined experience in the field, our team brings together talented engineers, physicists, and mathematicians from across Europe. We are driven by curiosity, technical excellence, and a shared ambition to build AI systems that make a tangible difference. /p pbAI Engineer /b, who will work with clients in the financial sector to bring AI solutions from prototype to production, with responsibilities spanning fine-tuning, deployment, inference optimization, monitoring, and continuous improvement. You will work in project teams alongside AI scientists, ensuring systems are reliable, scalable, and aligned with the high standards typical in banking. /p h3Working Location /h3 pThe role can be based in Zurich or Lugano.You must be willing to work onsite at least 80% of the time. Candidates must be based in Switzerland or willing to relocate to Switzerland. /p h3About the Role /h3 ul liYour responsibilities will span the full path from prototype to production - fine-tuning, deployment, inference optimization, monitoring, and continuous improvement of ML and LLM systems /li liProjects may involve LLM serving and inference stacks, cost/latency optimization, structured-output reliability, model monitoring pipelines, or productionizing solutions designed alongside AI scientists /li liYou will work in project teams alongside AI scientists, software engineering, infrastructure, and domain experts to integrate solutions smoothly into enterprise ecosystems using modern deployment tooling (Docker, Kubernetes, CI/CD) /li /ul h3Qualificationsand Skills: /h3 ul liMaster's degree in Computer Science, Engineering, or equivalent /li li3+ years of working experience as AI Engineer or in a similar role /li liExperience deploying and operating ML/LLM systems in production (serving, monitoring, cost/latency optimization) /li liStrong programming skills (Python, SQL) and familiarity with deployment tooling (Docker, Kubernetes, CI/CD) /li liFamiliarity with ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.) /li liHands-on experience with cloud platforms (AWS, Azure, or GCP) /li liProficiency in English /li /ul h3Nice to Have: /h3 ul liExperience with LLM inference stacks (e.g., vLLM) and structured-output reliability /li liFamiliarity with Databricks or distributed data frameworks. /li liExperience in finance or other regulated industries /li /ul h3Weoffer: /h3 ul liFull-timepermanentcontract /li liA stimulating scientific environment with an informal working atmosphere /li liMentorship and continuous learning and close relationship withcutting-edgeresearch teams /li /ul /p #J-18808-Ljbffr