Junior Machine Learning Engineer

Swissquote Bank SA

Gland, Vaud, Switzerland

Gland, Vaud, Switzerland

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Über

Building the bank of tomorrow takes more than means combiniJunior Machine Learning EngineerBuilding 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 Machine Learning EngineerOur AI systems X delivering measurable impact across the bank, from X models powering core business processes to a growing suite of LLM-powered transforming how teams work. As we scale this portfolio, we need engineers who can push the boundaries of possible while keeping production systems X Science team X for a Junior Machine Learning Engineer to design, build, and ship AI-powered solutions - with a strong emphasis on Large Language Model You will be involved in projects end-to-end: from X through to production-grade systems X users. This is a high-impact role where you will take on real responsibility early and shape how AI is built and delivered across the a Junior Machine Learning Engineer You Will:Build LLM-Powered Design and develop leveraging Large Language Models - including RAG systems, agentic workflows, and interfaces - tailored to complex business needs in a environment.Develop & Fine-Tune Models: Train, fine-tune, and both classical ML X models, selecting the right approach for each problem X for production constraints such as cost, and accuracy.Engineer for Production: Build reliable, scalable ML X APIs. You care about code quality, testing, and maintainability as much as model & Contribute to frameworks for AI - particularly for systems X metrics fall short - and use them X continuous on the Cutting Edge: Actively track the fast-moving LLM landscape, assess emerging tools and techniques (new model releases, frameworks, prompting and them X value for the Across Teams: Work closely with scientists and MLOps engineers, product owners, and business stakeholders to business problems X -scoped AI Background: Degree in Computer Science, Machine Learning, Science, Engineering, or a Proficiency: Strong programming skills in Python. You write clean, maintainable code and care about engineering best & NLP Experience: Hands-on experience building with Large Language Models (prompt engineering, RAG, fine-tuning, agent frameworks) - whether through professional experience, personal projects, or academic Fundamentals: Solid grounding in classical machine learning and deep learning. You can pick the right tool for the job, whether a gradient-boosted tree or a Comfort: You are able to build beyond the model - whether means spinning up an API, putting together a web interface, or wiring up a pipeline.Production Mindset: Familiarity with deploying models or into production. Experience with (Docker, Kubernetes) and CI/CD is a strong & Critical Thinking: You understand the challenges of AI systems X think critically about designing meaningful benchmarks beyond simple accuracy Fluent in English, able to effectively with both technical peers and non-technical to Have: Experience with MLflow, fine-tuning open-source LLMs, or frontend frameworks (React, Streamlit, Gradio). jid822773eaen jit0310aen jpiy26aen

Gland, Vaud, Switzerland

Sprachkenntnisse

English

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