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Swissquote

MLOps Engineer Intern

Swissquote is hiring a MLOps Engineer Intern. Level rates it ; you can apply on Swissquote.

Level's read on this job

  • Builds AI ●●●● is how Level rates this role: the job is building AI systems.
  • The posting mentions MLflow, AI agents and MLOps among its tools and skills.
  • Level classes it as an internship.
  • Swissquote has 34 other open roles on Level.
  • Posted in the last few days.

AI in this role

MLflow
ai-agentsml-opsai-research

At Swissquote, we’re all in.
All in to shake things up. All in to build the bank people actually want to use. All in to make finance less boring — and a lot more powerful.

We’re Switzerland’s leading digital bank — 1,500+ people across Europe, the Middle East and Asia, building real financial solutions for over a million clients worldwide. From trading and investing to everyday banking, we cover the full picture. We move fast, but we build things we’re genuinely proud of. Have a look behind the scenes by checking Humans of Swissquote on Instagram.

Growing fast creates room. Room to try things, own things, and grow at a pace most places can’t offer. Whether you like the spotlight or prefer to just put your head down and do great work, there’s space for both here.

We’ve ditched the dress code — but never the chance to celebrate. Big win or small, we make it count. The kind of place where the atmosphere takes care of itself.

As an equal opportunity employer, we welcome candidates from all backgrounds, experiences and perspectives to join our team and contribute to our shared success.

Feeling it? It’s a good start. Apply.

    The AI Research & Solutions department at Swissquote is looking for an MLOps Intern to help bring AI applications from experimentation to reliable, scalable production.

    You will gain hands-on experience across the AI lifecycle, with a strong focus on the infrastructure and tooling behind LLM applications and AI agents, alongside traditional machine learning models.

    During your internship, you will:

    • Improve monitoring and evaluation: Help automate the evaluation and monitoring of deployed AI applications. Develop observability for LLM responses, agent workflows and tool interactions, tracking quality, reliability, latency and cost.
    • Build deployment tooling: Contribute to our internal MLflow-based platform, helping engineers version, package and deploy models and agents on our infrastructure.
    • Automate pipelines: Build and improve reproducible data, training and evaluation pipelines using Argo Workflows, and contribute to automated testing and deployment.
    • Support AI governance: Help develop internal tools for tracking deployed AI applications, improving traceability and supporting company governance and compliance requirements.
    • Ongoing studies in Computer Science, Data Science, Engineering or a related field.
    • Good Python skills and an interest in writing maintainable software.
    • Familiarity with—or a strong motivation to learn—CI/CD, GitHub Actions, Docker and Kubernetes.
    • Curiosity about LLMs and AI agents, particularly how they are deployed, evaluated and monitored in production.
    • An organized, proactive approach, a willingness to learn and the ability to collaborate effectively in English.

    Experience with frontend development is a plus, as you may also contribute to interfaces for internal tools.

    "Please note that Swissquote never requests sensitive personal information or payment of any kind during the recruitment process. Any such request is fraudulent.”

    How we rate this

    MLOps Engineer Intern at Swissquote rates 91 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

    Classification

    Builds AI. The job is building AI systems.

    1. ●●●● Builds AI80 to 100
    2. ●●●○ Works on AI60 to 79
    3. ●●○○ Uses AI40 to 59
    4. ●○○○ Little AI0 to 39

    Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

    Prepare for this job

    Built from this posting and from similar jobs on Level.

    Skills and AI tools this role asks for

    AI agentsML OpsAI ResearchMLflow

    Questions you could be asked

    1. How do you decide when an AI agent can act on its own versus asking for approval first?
    2. How do you monitor a model once it's live, and how do you know it needs retraining?
    3. Tell me about a research question you investigated. What did you find?
    4. What's a project where you used MLflow hands-on?
    5. How would you decide a model or AI system is ready to ship?

    Adapt your resume

    • List these exact terms on your resume: AI agents, ML Ops, AI Research, and MLflow. An applicant tracking system matches the wording, not the idea.
    • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
    • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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