17 meilleures offres (devops engineer cloud devops platforms) (à pourvoir)

GenAI & Machine Learning Engineer
Ethinc —Lausanne, VD
- Travail hybride
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- Niveau Master
- Bases de données
Postuler rapidement
13 h
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- 100%
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Senior Java Developer (Distributed Financial Systems) 80 - 100% (f/m/d) - (Contract through our external payroll partner with immediate start for 12 months with possible extension)
Julius Baer —Zürich, ZH
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Prime21 AG —Suisse
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Staff Engineer, Platform & Infrastructure
Nango —Suisse
- De 140 000 CHF à 220 000 CHF par an
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- Technologies de l'information
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Staff Platform Engineer
Nango —Suisse
- De 140 000 CHF à 220 000 CHF par an
- 100%
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Then contact our Recruiting Team via email at [email protected]. Supporting application teams in adopting DevOps and cloud-native practices.
GenAI & Machine Learning Engineer
Ethinc —Lausanne, VD
If you have questions about the position, you can reach us via our contact form. Ethinc processes the personal data submitted through applications solely for…
Postuler rapidement
13 h

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GenAI & Machine Learning Engineer

Ethinc
Lausanne, VD

Postuler rapidement

Détails de l'emploi

Intérim
Il y a 13 heures

Qualifications

Français
Anglais
Niveau Master
Bases de données
SQL
Docker
Python

Description complète du poste

About Ethinc

Ethinc is an AI & data consultancy based at EPFL Innovation Park in Lausanne. Founded by EPFL alumni and industry engineers, we build AI systems that hold up in real organizations: custom internal tools, machine learning, computer vision, and production-grade deployments shaped around client workflows, data, and constraints. Our projects span multiple industries, and we work closely with clients from day one through delivery and maintenance.

Learn more about our work, expertise, and approach at ethinc.ch.

The role

We are looking for a GenAI & ML Engineer who can contribute across the full AI development lifecycle: from backend systems and data pipelines to machine learning models, LLM applications, deployment, and technical documentation.

You will work on real client projects where AI, data engineering, software architecture, and practical deployment constraints meet.

You will contribute to systems involving APIs, data processing, model development, LLM integration, retrieval-augmented generation, computer vision, automation workflows, and internal tools for client organizations. Depending on the project, you may work on prototypes, production deployments, monitoring, evaluation, or maintenance of existing systems.

What you will work on

You will contribute to projects involving:

backend systems and APIs supporting AI and data applications;
Python-based services using frameworks such as FastAPI, Flask, or similar;
machine learning pipelines, model training, evaluation, and deployment;
LLM-powered applications, including prompt engineering, structured outputs, tool use, and retrieval-augmented generation;
vector search, embeddings, semantic search, and document-processing workflows;
data pipelines involving SQL, Python, APIs, files, object storage, and structured/unstructured data;
computer vision or image-processing workflows where relevant;
DevOps and deployment for AI/ML workloads using tools such as Docker, CI/CD, cloud services, or containerized environments;
monitoring, testing, debugging, and improving deployed AI systems;
internal tools and dashboards for client organizations;
technical documentation, handover material, and client-facing explanations.

What we look for

We are looking for someone with a strong technical foundation and the ability to learn across domains. You should have:

solid programming skills, especially in Python;
understanding of machine learning fundamentals and practical model development;
familiarity with backend development, APIs, databases, and data processing;
interest or experience in LLM applications, RAG systems, embeddings, or AI agents;
ability to work with messy real-world data and turn it into usable systems;
Some level of comfort navigating ambiguity, changing requirements, and multiple projects at the same time;
Professional working proficiency in English and French;
ability to explain technical topics clearly to both technical and non-technical stakeholders;
client-facing confidence, or the willingness to develop it;
a serious, reliable, and pragmatic approach to engineering;
availability to work on-site in Lausanne, or willingness to relocate.

Nice to have

It would be a plus if you have experience or interest in one or more of the following:

MLOps, model deployment, monitoring, or evaluation;
cloud platforms, Kubernetes, Docker, CI/CD, or infrastructure-as-code;
data engineering tools and workflows;
computer vision, OCR, document AI, or image-processing systems;
client-facing technical work, consulting, internships, or project-based delivery;
academic or applied projects in AI, data science, software engineering, or computer science.

You do not need to know everything already. We care more about strong foundations, learning speed, judgment, and the ability to build responsibly than about checking every box.

What we offer

A strong learning environment with direct access to experienced engineers and AI/data specialists;
Real projects with real users, real constraints, and measurable impact;
Exposure to the full lifecycle of AI systems, from early scoping to production deployment;
A small, collaborative team with high standards and genuine respect for working conditions;
Direct involvement in client discussions and technical decision-making;
A workplace at EPFL Innovation Park, at the center of Switzerland’s AI, research, and deep-tech ecosystem;
A culture built on trust, intellectual honesty, responsibility, and room to grow.

Practical information

Employment rate: Full-time, 100%
Contract: Fixed-term employment contract
Contract duration: 4 months
Expected start: 1st of October 2026
Location: EPFL Innovation Park, Lausanne
Working arrangement: Hybrid

How to apply

Send your CV and a brief cover note.

Tell us what actually draws you to this role, what you have built or worked on before, and what you believe you could bring to Ethinc. We are more interested in how you think, learn, and communicate.

Be clear. Be specific. Be yourself.

If you have questions about the position, you can reach us via our contact form.

Candidate Data

Ethinc processes the personal data submitted through applications solely for recruitment purposes. Access is limited to the people involved in the selection process.

Applications that are not retained will be deleted after the recruitment process unless the candidate agrees to their information being retained for future opportunities. References will only be contacted with the candidate’s prior consent.

Ability to commute/relocate:

1015 Lausanne, VD: Reliably commute or planning to relocate before starting work (Required)

Education:

Master's (Required)

Experience:

Python: 2 years (Required)
Machine Learning: 2 years (Required)

Language:

English (Required)
French (Required)

Location:

1015 Lausanne, VD (Preferred)

Work Location: Hybrid remote in 1015 Lausanne, VD

Postuler rapidement

Affinez votre recherche

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