All active LLM roles based in Switzerland.
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Company Overview:
Dialectic, a crypto-native organization of builders and capital advisors, is seeking an AI-native Operations & Admin Intern to join the team on a full-time basis in Zug. This is a great opportunity to join a dynamic and fast-growing team focused on investing in and building compelling software in emerging crypto and blockchain technologies.
Dialectic acts as an advisor to multiple liquid crypto funds specializing in DeFi yield strategies, as well as venture activity focused on crypto/blockchain technologies. Additionally, Dialectic stewards 1OF1, a prominent digital art collection.
Job Summary:
We are looking for a highly organized, AI-native self-starter to support operations and administrative functions across the organization - including direct support to our founder. The ideal intern candidate is fluent in modern AI tools (LLMs, agents, copilots) and uses them as a default part of every workflow: from inbox triage and research to drafting documents to consolidating data and automating recurring processes. You’ll touch a bit of everything, which requires a “no job too big or too small” attitude. This role is ideal for someone curious about crypto, finance, and operations who wants to learn the ins and outs of a multi-strategy investment firm while building real AI-driven workflows.
Key Responsibilities:
Key Requirements:
Nice-to-haves:
Benefits:
Dialectic offers an exceptional work culture:
Ready to apply?
Apply to DialecticArtefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.
With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.
As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.
Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.
Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).
DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).
Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.
Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.
The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).
AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).
Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).
Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.
Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
Nice to have
Experience with responsible AI/governance frameworks, security reviews, and cost optimization.
Domain experience in finance.
Contributions to open-source, publications, or conference talks.
Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.
Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.
Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.
Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.
Location: Zurich
If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.
Ready to apply?
Apply to ArtefactShare this job
Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.
With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.
As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.
Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.
Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).
DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).
Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.
Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.
The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).
AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).
Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).
Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.
Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
Nice to have
Experience with responsible AI/governance frameworks, security reviews, and cost optimization.
Domain experience in finance.
Contributions to open-source, publications, or conference talks.
Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.
Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.
Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.
Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.
Location: Zurich
If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.
Ready to apply?
Apply to LinkedIn Job WrappingShare this job
Artefact is a next-generation strategy and data consulting firm dedicated to transforming organizations through data and AI. We combine the rigor of top-tier strategy consulting with deep expertise in data, digital, and analytics to help clients achieve tangible business impact.
With 1,800+ consultants, data scientists, and engineers across 23 countries, we work with global leaders such as Samsung, L’Oréal, Orange, and Sanofi. Our Romandie office (Geneva/Lausanne) is at the heart of Artefact’s growth, advising clients on their most pressing strategic challenges — from AI strategy and governance to digital transformation roadmaps and new business model design.
As a Senior AI & Data Engineer, you will be the architect of the "AI Factory." Your role is less about training models from scratch and more about building the industrial-grade pipelines, infrastructure, and security frameworks required to run AI in a highly regulated environment.
Production-Grade AI Infrastructure: Design and implement robust MLOps and LLMOps pipelines specifically for banking environments, focusing on data residency, air-gapping possibilities, and high availability.
Data Engineering for AI: Build scalable ETL/ELT pipelines to feed RAG (Retrieval-Augmented Generation) systems, ensuring data lineage, quality, and strict access control (RBAC).
DevOps & Automation: Own the CI/CD lifecycle for AI assets. Automate the deployment of model APIs, vector databases, and monitoring stacks using Infrastructure as Code (IaC).
Hybrid Cloud & On-Prem: Navigate complex hybrid-cloud architectures (Azure/AWS/GCP vs. Private Cloud) common in Swiss banking.
Technical Advisory: Act as a bridge between IT Infrastructure, Risk/Compliance, and Business units to translate AI potential into stable, governed reality.
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
The "DevOps" Stack: Expert knowledge of Docker, Kubernetes (K8s), and CI/CD tools (GitHub Actions, GitLab CI, or Jenkins). Experience with Terraform or Pulumi is a strong plus.
The "Data" Stack: Advanced SQL and Python. Deep experience with data orchestration (Airflow, Dagster), streaming (Kafka), and modern data warehouses (Snowflake, Databricks).
AI/LLM Implementation: Hands-on experience with the "plumbing" of AI: Vector databases (Milvus, Qdrant, or pgvector), model serving (BentoML, vLLM), and RAG orchestration (LangChain/LlamaIndex).
Banking Domain: Solid understanding of financial data structures and the regulatory landscape (Model Risk Management, Audit trails, Data anonymization).
Languages: English is mandatory. German (B2 or higher) is a significant advantage for the Zurich market and stakeholder management.
Education: Master’s degree in Computer Science, Software Engineering, or a related quantitative field.
Nice to have
Experience with responsible AI/governance frameworks, security reviews, and cost optimization.
Domain experience in finance.
Contributions to open-source, publications, or conference talks.
Strategy with a Data Edge: Operate at the intersection of boardroom strategy and cutting-edge AI engineering.
Zurich Office Impact: High visibility from day one; help shape our Swiss footprint and work directly with senior leadership.
Learning & Growth: Advanced training across strategy, AI/ML/LLM, and cloud; international missions and communities of practice.
Culture of Doers: Innovation, action, collaboration. We move fast, deliver impact, and support each other’s growth.
Location: Zurich
If you don’t meet 100% of the criteria, we still want to hear from you. Passion, curiosity, and impact orientation matter — tell us about yours.
Ready to apply?
Apply to Welcome to the JungleAt Google DeepMind, we value diversity of experience, knowledge, backgrounds and perspectives and harness these qualities to create extraordinary impact. We are committed to equal employment opportunity regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, pregnancy, or related condition (including breastfeeding) or any other basis as protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know.
Snapshot
The Gemini Safety team is accountable for the safety and fairness behavior of GDM’s latest Gemini models. The role of the Research Scientist will be to apply and develop data and algorithmic cutting edge solutions to advance GDM’s latest user-facing models. The workstyle is fast paced, and highly collaborative. The team has a strong culture of support, dedication and collaboration.
About Us
Artificial Intelligence could be one of humanity’s most useful inventions. At Google DeepMind, we’re a team of scientists, engineers, machine learning experts and more, working together to advance the state of the art in artificial intelligence. We use our technologies for widespread public benefit and scientific discovery, and collaborate with others on critical challenges, ensuring safety and ethics are the highest priority.
The role
We’re looking for a versatile Research Scientist, at ease both with figuring out how to approach new research questions, and the technical implementation of research ideas.
Our team focuses on advancing the safety and fairness behaviour of state of the art AI models. We drive the development of the foundational technology adopted by numerous product areas including Gemini App, Cloud API, and Search.
Key responsibilities:
About you
In order to set you up for success as a Research Scientist in the Gemini Safety team, we look for the following skills and experience:
In addition, the following would be an advantage:
Ready to apply?
Apply to DeepMindCookies & analytics
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