Staff MLOps Engineer (AIML Platform)

The Role

Were hiring a Staff MLOps Engineer to own the AI/ML platform at Cint. The immediate focus is supporting the Synthetic Data Platform models for survey augmentation and respondent profiling but the roles longer-term remit is broader: Trust Score (our respondent quality and fraud detection model) and other AI/ML initiatives need the same platform capabilities. Youll start by reviewing the current setup and deciding whether to extend it or rebuild parts of it then build out the shared AI/ML platform from there.

The Team

Youll report into our Infrastructure and Data Engineering organisation working in close partnership with the AI/ML team in Prague. This is deliberately a platform-with-feature-focus role: your day-to-day delivery serves the Synthetic Data teams needs but your architectural remit covers all of Cints AI/ML workloads.

Qualifications :

What Youll Do

• Assess and decide on the current pipeline: Audit the existing AI/ML training and serving setup. Decide whats worth building on and what needs to be rebuilt. Make the call and own the rationale.

• Build the shared AI/ML platform: Training infrastructure experiment tracking model registry serving monitoring. Built once used by Synthetic Trust Score and whatever comes next.

• Oversee the full ML lifecycle: From data ingestion and feature processing to annotation workflows ensuring the platform facilitates frictionless rapid model iteration for Data Scientists.

• Own training infrastructure on Databricks and Unity Catalog: Make training fast reproducible and traceable. Lineage matters; reproducibility matters more.

• Model serving: Build the serving layer low-latency APIs batch scoring jobs appropriate caching. Integrate with our Java/Spring services.

• Monitoring and drift: Build the observability our models need data drift model drift accuracy regression business metrics. Grafana dashboards Prometheus metrics clear alerts.

• Cost and performance: ML compute costs add up. Set the patterns for cost-effective training and serving representing ML infrastructure spend and ROI credibly to finance stakeholders.

• Mentor and multiply: Act as a force multiplier by coaching AI/ML and Infrastructure engineers on engineering best practices. You dont just do the work; you set the bar for what good looks like.

• Drive AI tooling adoption: Model how AI-native development works for platform teams. Claude Code agentic workflows AI-assisted incident response.

• Databricks / Spark Native: Comfortable in Databricks. Unity Catalog experience is a strong plus.

• Kubernetes & Cloud: Youve deployed ML workloads on Kubernetes. AWS (EKS) is our environment; familiarity is a plus.

• Be a Polyglot: Python Scala or Java (for Spark) Kubernetes manifests Terraform. AWS or GCP. You move between layers without friction.

Who You Are

• Deep ML Platform Expertise: Youve led ML platform work at a serious scale. You have strong opinions on feature stores model registries serving patterns and what ML observability actually means.

• Mature Engineering: Youre someone with both a wide and deep background of engineering excellence in a number of disciplines. This is a very senior position in our engineering organisation; setting examples in approach and behaviour is a key trait.

• Systems Architect: You think about the platform as a product with real users (your ML team). You design APIs write docs and measure adoption.

• Technical leader: You lead through standards RFCs and credibility not meetings. Youve mentored MLOps engineers into senior ICs.

• Pragmatic about buy-vs-build: You know when to adopt a managed service and when to build. You can defend either call to leadership.

• Commercially literate: You can justify platform investment to VP / C-suite and translate business priorities into a roadmap.

Additional Information :

Working at Cint

• Prague-First Europe-Friendly: Our preferred base is Prague alongside our existing AI/ML team. Remote work from Germany Spain or the UK is also possible these are the markets where we have entities.

• AI-Native Engineering: Were rolling out Claude Code and modern agentic tooling across engineering. Youll use it daily not as a novelty but as a force multiplier for the complex problems that matter.

• High Autonomy: We trust our engineers to make sound decisions and own their work end-to-end.

• Global Impact: Your work powers a marketplace used by millions of people worldwide.

   

Our Values

Collaboration is our superpower

• We uncover rich perspectives across the world
• Success happens together
• We deliver across borders.

Innovation is in our blood

• Were pioneers in our industry
• Our curiosity is insatiable
• We bring the best ideas to life.

We do what we say

• Were accountable for our work and actions
• Excellence comes as standard
• Were open honest and kind always.

We are caring

• We learn from each others experiences
• Stop and listen; every opinion matters
• We embrace diversity equity and inclusion.

More About Cint

Were proud to be recognised in Newsweeks 2025 Global Top 100 Most Loved Workplaces reflecting our commitment to a culture of trust respect and employee growth.

In June 2021 Cint acquired Berlin-based GapFish the worlds largest ISO certified online panel community in the DACH region and in January 2022 completed the acquisition of US-based Lucid a programmatic research technology platform that provides access to first-party survey data in over 110 countries.

Cint Group AB (publ) listed on Nasdaq Stockholm this growth has made Cint a strong global platform with teams across its many global offices including Stockholm London New York New Orleans Singapore Tokyo and Sydney. ()

Additionally in a world of AI we want our candidates to understand our approach to the use of AI during the interview and hiring process so wed appreciate you reading our AI usage guide.

Remote Work :

Yes

Employment Type :

Full-time