MLOps Jobs in Switzerland.
All active MLOps roles based in Switzerland.
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Director of Platform Engineering
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The climate crisis is the defining challenge of our time—but it’s also the greatest opportunity for innovation, and a challenge we’re proud to take on. At Overstory, we’re harnessing cutting-edge technology to enable a resilient electrical grid that keeps communities thriving as our world changes.
The grid is the backbone of life as we know it. It powers hospitals, keeps food fresh, and ensures communities stay connected. But extreme weather, aging infrastructure, and growing wildfire risks are putting this critical system under pressure. All of this combined makes the electric utility industry the greatest opportunity for tackling climate change.
One of the leading causes of catastrophic wildfires and power outages? Trees and brush coming into contact with power lines.
That’s where we help. At Overstory, we use AI and advanced satellite imagery to pinpoint and prioritize vegetation risks before they materialize. By giving utilities critical analysis on those risks, we’re helping prevent outages, reduce wildfire risks, and accelerate the transition to a safer, more resilient grid.
Our team spans the Americas and Europe, and we work with utility partners across the Americas and beyond. We’re outdoor enthusiasts, musicians, artists, athletes, parents, and adventurers. What unites us is a passion for solving complex problems, a commitment to climate action, and the belief that technology should be a force for good.
Join us to help us build a more resilient world together.
Role & Team
We’re looking for a Director of Platform & Infrastructure to own and evolve our core engineering foundations. Reporting to our VP of Product Engineering, this role will lead SRE, MLOps, and Platform teams with a mandate to create leverage across the entire organization.
As a scaling startup, we’re evolving from early-stage infrastructure to a more mature, reliable platform that can support rapid product development and growing customer demand. This role is critical in helping us make that transition — building systems, standards, and teams that enable speed today while laying the foundation for long-term scale.
Partnering closely with product, data, and application engineering teams, you will set the technical vision, define best practices, and ensure our infrastructure enables teams to move fast with confidence.
This is a highly cross-functional leadership role for someone who combines deep technical judgment with a systems mindset, strong people leadership, and a passion for building platforms that empower others.
Time zone requirement: Europe (GMT/WET, CET, EET) and Eastern North America (NST, AST, EST)
What You'll Do
- Own the platform strategy across Platform, MLOps, and SRE, aligning it with company and product goals
- Grow senior ICs (and eventually manages) across multiple teams, fostering strong technical leadership and healthy team cultures
- Define and evolve our platform vision, including developer experience, internal tooling, CI/CD, infrastructure, observability, and reliability standards
- Oversee MLOps systems that support model development, training, deployment, monitoring, and governance in production
- Partner cross-functionally with Product, ML, Data, Security, and Compliance to ensure the platform meets current and future needs
- Balance speed and stability, making thoughtful tradeoffs between innovation, cost, reliability, and operational excellence
- Set metrics and accountability for platform performance, reliability, and developer productivity
Skills & Experience
- 10+ years experience leading platform, infrastructure, or reliability teams in a scaling startup environment, including navigating ambiguity, rapid growth, and the transition from early-stage systems to more mature, repeatable platforms
- Strong understanding of cloud-native infrastructure (GCP strongly preferred), Kubernetes, CI/CD, and modern DevOps practices
- Experience supporting machine learning systems in production, including model deployment, monitoring, and lifecycle management
- A track record of building reliable, scalable systems used by fast-moving product teams
- Excellent people leadership skills — you know how to coach managers, grow talent, and build inclusive, high-performing teams
- Strong communication skills and the ability to influence across org boundaries
- Experience in data- or ML-heavy products
Nice To Have
- Experience with geospatial data, image processing or mapping technology
Note: We believe that all people are capable of great things. We encourage you to apply even if you do not meet all of the requirements that are listed within this job description.
What We Offer
- Competitive, location-specific compensation and benefits.
- Flexible, autonomous and collaborative working environment rooted in trust - we build our work days around our lives, not the other way around
- Home office stipend, coworking and ongoing education budgets
- A company culture that genuinely embodies each of our core values
- To be part of truly mission-driven work that reduces wildfires, protects earth’s natural resources and helps solve our climate crisis
About Our Team
We are a group of 100 people from all over the world. Fifteen nationalities are represented in our team and at last count we speak fourteen languages: English, Dutch, French, Spanish, German, Italian, Portuguese, Russian, Luxembourgish, Lithuanian, Bulgarian, Cantonese, Estonian, and Danish.
We work remotely from eleven countries and are looking for candidates that are living and working in one of them: United States, the Netherlands, United Kingdom, Ireland, Estonia, Portugal, France, Sweden, Switzerland, Denmark and Canada. We gather once a year in-person for our unforgettable team gathering event. We also offer the option to occasionally meet up for in-person collaboration.
Diversity & Inclusion
The climate crisis is a human crisis that requires diverse perspectives to solve.
We place enormous value on diversity and believe that the best ideas emerge when people with different backgrounds and experience work together. We remain committed to scaling a team that reflects the communities we serve, and strive to uphold equitable and inclusive practices across every aspect of our business. We are responsible for creating and maintaining a culture where everyone - regardless of background - has a voice in building a sustainable future.
Our Values
Tackling the climate crisis is our greatest mission.
We act with urgency.
Our curiosity fuels our growth.
We recognize that change is constant, and we find joy and power in exploration.
We’re rooted in diversity.
Just as ecosystems need biodiversity to thrive, our resiliency comes from our differences.
We care for each other.
We love the power of machines but we nurture each other as humans.
Trust is fundamental.
We assume the best in everyone, and we share ideas openly so that we have a positive impact.
_________________________________
Use of AI in Our Hiring Process
We sometimes use AI tools to support parts of our hiring process, such as helping us manage applications more efficiently or ensuring job descriptions are clear and inclusive. All hiring decisions are always made by people, not machines. Any data processed by AI is handled securely in line with GDPR and our Privacy Notice.
Ready to apply?
Apply to Overstory
Who is Artefact?
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.
Main Responsibilities
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.
Candidate Profile
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
- Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.
-
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.
Why Join Us
-
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 ArtefactSenior AI Engineer / Technical Consultant
Share this job
Who is Artefact?
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.
Main Responsibilities
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.
Candidate Profile
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
- Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.
-
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.
Why Join Us
-
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 WrappingSenior AI Engineer / Technical Consultant
Share this job
Who is Artefact?
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.
Main Responsibilities
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.
Candidate Profile
Engineer first, consultant second — with a builder’s mindset and a track record of shipping.
- Experience: 4+ years in Data Engineering, DevOps, or Software Engineering, with at least 2 years focused on deploying Machine Learning or AI systems at scale.
-
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.
Why Join Us
-
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 Jungle