<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> <p>Artificialy is 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><p><br/></p><p>Founded 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><p><br/></p><p>We are looking for a <strong>Machine Learning Engineer</strong> who will work with clients in the financial sector to design, develop, and operationalize data-driven solutions.</p><p><br/></p><p>For this role you must be willing to work at least 80% onsite in our office and potentially on client’s site.</p><p><br/></p><p><strong>About the Role</strong></p><ul><li>Your responsibilities will span the full lifecycle of ML initiatives spanning from early experimentation to deployment, monitoring, and continuous optimization.</li><li>Projects may involve automated or agentic analytical pipelines, forecasting models, anomaly-detection systems, or other statistical and machine-learning solutions.</li><li>Much of the work will run within cloud-based environments, where you will ensure that pipelines and models are reliable, scalable, and aligned with the high standards typical in banking.</li><li>You will collaborate with software engineering, infrastructure, and domain teams to integrate solutions smoothly into enterprise ecosystems.</li></ul><p><br/></p><p><strong>Qualifications and Skills</strong></p><ul><li>Master’s degree or PhD in Computer Science, Mathematics, Physics, Informatics, Engineering, or equivalent discipline.</li><li>2+ years of experience as ML Engineer<strong> </strong>or similar</li><li>Strong programming skills (Python, SQL, …) and familiarity with ML libraries (TensorFlow, PyTorch, Scikit-learn, etc.).</li><li>Solid understanding of ML principles, statistical modeling, and modern data-processing techniques.</li><li>Hands-on experience with cloud platforms (AWS, Azure, or GCP) and with deploying ML systems in scalable, production-grade environments.</li><li>Experience with data visualization tools (e.g., Tableau, Matplotlib).</li><li>Familiarity with Git-based development workflows (GitHub/GitLab/Bitbucket).</li><li>Proficiency in English.</li></ul><p><br/></p><p><strong>Nice to have</strong></p><ul><li>Familiarity with cloud ML services and hybrid cloud architectures (e.g., AWS SageMaker, Azure ML, Vertex AI).</li><li>Knowledge of deployment and orchestration tools (Docker, Kubernetes, CI/CD).</li><li>Understanding of data systems and architectures (e.g., PostgreSQL, distributed data frameworks).</li><li>Proficiency in Italian or German; French is a plus.</li></ul><p><br/></p><p><strong>We offer</strong></p><ul><li>Full-time permanent contract</li><li>Competitive compensation and growth opportunities</li><li>A stimulating scientific environment with an informal working atmosphere</li><li>Mentorship and continuous learning</li></ul> </div>