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Staff MLOps Engineer (AI/ML Platform)
CCint
Summary by AIEngineer.careers
Staff MLOps Engineer (AI/ML Platform) is a MLOps Engineer role (full-time). with Cint. in REMOTE, WORLDWIDE. Imported listing (source: careersync.liveblog365.com). Apply on the employer's site (careersync.liveblog365.com).
Imported listing (source: careersync.liveblog365.com) · Apply on careersync.liveblog365.com
REMOTE · WORLDWIDE
—
Full-time
STAFF
The sections below reproduce the third-party job description for reference. AIEngineer.careers does not write or control this text.
Imported job description
Sourced from careersync.liveblog365.com
Cint is hiring a Staff MLOps Engineer to own the AI/ML platform, supporting synthetic data and respondent quality models. The role focuses on building shared ML infrastructure on Databricks, Kubernetes, and AWS. You will mentor engineers and drive AI-native development practices.
Responsibilities
- Audit existing AI/ML training and serving setup, decide what to build on or rebuild
- Build shared AI/ML platform: training infrastructure, experiment tracking, model registry, serving, monitoring
- Oversee full ML lifecycle from data ingestion to annotation workflows
- Own training infrastructure on Databricks and Unity Catalog
- Build low-latency model serving layer with caching, integrate with Java/Spring services
- Implement monitoring for data drift, model drift, accuracy regression, business metrics
- Manage ML compute costs and represent infrastructure spend to stakeholders
- Mentor AI/ML and Infrastructure engineers on best practices
- Drive AI tooling adoption (Claude Code, agentic workflows)
Requirements
- Deep ML Platform expertise at serious scale, with strong opinions on feature stores, model registries, serving patterns, ML observability
C
Cint
Stockholm · SE · 640+ employees
Cint is a global technology company that provides a platform for continuous research and measurement. It connects researchers, advertisers, and brands to a vast network of high-quality consumer data to facilitate rapid business decisions.
