Junior ML Ops Engineer

Swissquote Bank SA

Gland, Vaud, Switzerland

Gland, Vaud, Switzerland

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About

Building the bank of tomorrow takes more than means combiniJunior ML X the bank of tomorrow takes more than means combining our differences to imagine, discuss, code, develop, test, learn and every step together. Share our vibes? Join Swissquote to unleash your are the Swiss Leader in Online Banking and we provide trading, investing and banking services to clients through our performant and secured digital employees work in a flexible way, without dress code and in multicultural having a huge impact on the industry, they are growing their skills portfolio and boosting their career in a fast-pace environment. Have a look behind the scenes by checking Humans of Swissquote on are all As an equal opportunity employer, we welcome X backgrounds, experiences and perspectives to join our team X to our shared you all in? Don t be shy, apply!Junior ML X our portfolio of production AI systems X grow, so does the need for engineering excellence around reliability, scalability, and governance. To sustain this momentum, X strengthening the team X models run seamlessly in production-delivering value every day while meeting the highest standards of compliance and Science team X for a Junior MLOps Engineer to help improve and streamline the lifecycle of our AI models, from X production. This role is particularly exciting because you will not be limited to a single domain; you will work across a diverse array of topics surrounding production-deployed models, gaining deep hands-on experience with the entire lifecycle of an AI joining the team, X contribute to building the backbone supports the bank s AI capabilities, ensuring efficiency and governance across the a Junior MLOps Engineer You Monitoring & Observability: Develop systems X of deployed AI You will work on improving observability for both classical Machine Learning models and Models, ensuring we have real-time X performance and Deployment Contribute to the development of an internal based on MLflow. You will help streamline the developer experience by tools for model and agent versioning, packaging, and seamless deployment onto our internal Pipelines: Design, optimize, and complex and training pipelines using Argo Workflows, ensuring our model training processes are reproducible and efficient.Enforce AI Governance: Help build a governance acts as a central control plane, ensuring all deployed AI strictly adhere to company and compliance Background: Degree in Computer Science, Science, Engineering, or a Proficiency: Strong command of Python; you write clean, maintainable code and care about engineering best Understanding of DevOps concepts such as CI/CD (GitHub Actions) and (Docker, Kubernetes). Prior hands-on experience is a strong plus.Infrastructure Mindset: You are by happens after the model is trained -specifically how models are deployed, scaled, and monitored in production Development Awareness: Familiarity with frontend development is a plus (for building internal tools and dashboards).Growth Mindset: You are organized, and comfortable ramping up quickly on new technologies and Fluent in English and able to effectively within a technical team. jid596493daen jit0310aen jpiy26aen

Gland, Vaud, Switzerland

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English

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