Staff MLOps Engineer, Cint
AI/ML Platform
Research and measurement technology
Be an early applicant
Research and measurement technology
501-1000 employees
Be an early applicant
501-1000 employees
Company mission
To automate the insights gathering process so that companies can gain access to insights faster with unparalleled scale.
Role
Who you are
- Deep ML Platform Expertise: You've 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: You’re 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. You've 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
What the job involves
- We're 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 role's longer-term remit is broader:
- Trust Score (our respondent quality and fraud detection model) and other AI/ML initiatives need the same platform capabilities
- You'll 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
- You'll 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 team's needs, but your architectural remit covers all of Cint's AI/ML workloads
- Assess and decide on the current pipeline: Audit the existing AI/ML training and serving setup. Decide what's 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 don’t 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: You've 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
Our take
Cint is a market leader in digital insights gathering and acts as a catalyst for the digitalisation of the insights industry. Its area of expertise is the automation of the insight gathering process, allowing businesses to leverage insights faster at a lower cost.
Cint manages the world's largest consumer network for digital survey-based research - more precisely, companies use Cint's platform to connect with supply partners that provide insights on target audiences collected via online surveys.
The company serves thousands of B2B clients, counting Zappi, Syno, Nielsen, Statista and SurveyMonkey. It's also seen rapid growth and has achieved a market-leading position due to significant investment in its platform, expansion into the US, and its acquisition of GapFish, P2Sample, Thumbspeak, and Lucid.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (2 rounds)
Sep 2010
$13m
SERIES B
Nov 2007
$3m
SERIES A
Total funding: $16m
Company HQ
Norrmalm, Stockholm, Stockholms län
Leadership
Patrick Comer
(CEO)Patrick is also the Founder and Patron of Grpnr as well as a Partner at restecher. Previously, they Founded Lucid where they served as the CEO for 12 years.
Niels Boon
(CFO)Prior to joining Cint in 2024, Niels was the Managing Director & CFO at Zenjob, CFO at GoodieBox, and Chief Financial & Operating Officer at Ada Health.
Bregje Meuwissen
(CPO)Prior to joining Cint in 2023, Bregje was the Vice CPO at DocPlanner, VP of HR, Middle East & Africa at IDEMIA and the EMEA HR Director at Travelport.
Michelle joined Cint in 2022 as a Senior VP of Global Customer Experience, moving into the role of EVP of Global Customer Experience in 2023 and CXO in 2024. Prior to Cint, they spent 7 years at Lucid as a Senior Director and VP of Customer Success & Product Specialists.
Alesia Braga
(Chief Product & Technology Officer)Alesia is also an Advisor at Paul's Job. Previously, they were the CTO at SmartRecruiters and Quandoo. They also spent 1 year at Google working in Technical Program Management for Google Cloud.
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