Staff MLOps Engineer – AI/ML Platform

🕒 June 25

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Logo of Cint

Cint

1001 - 5000 employees

Founded 2004

🤝 B2B

☁️ SaaS

💰 Venture Round on 2016-01

Market Research • B2B • SaaS

Cint is a leading global technology platform that provides a comprehensive marketplace for market research. The company operates the world's largest programmatic research marketplace, known as the Cint Exchange, which connects surveys with millions of respondents across 130 countries. Cint offers services such as media measurement and audience monetization, leveraging powerful technology to provide insights-driven companies with actionable data. With a focus on quality and trust, Cint uses advanced AI and machine learning tools to ensure the integrity and accuracy of the data collected. It serves a wide range of industries by offering tools for measuring the impact of advertising, conducting brand lift studies, and optimizing marketing strategies in real time. Cint is trusted by thousands of companies for its innovative approach to connecting businesses with the right survey participants efficiently and effectively.

📋 Description

• Assess and decide on the current pipeline: Audit the existing AI/ML training and serving setup. • Build the shared AI/ML platform: Training infrastructure, experiment tracking, model registry, serving, monitoring. • Oversee the full ML lifecycle: From data ingestion and feature processing to annotation workflows. • Own training infrastructure on Databricks and Unity Catalog: Make training fast, reproducible, and traceable. • 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.

🎯 Requirements

• Deep ML Platform Expertise: You've led ML platform work at a serious scale. • Mature Engineering: You’re someone with both a wide and deep background of engineering excellence in a number of disciplines. • Systems Architect: You think about the platform as a product with real users (your ML team). • Technical leader: You lead through standards, RFCs, and credibility — not meetings. • Pragmatic about buy-vs-build: You know when to adopt a managed service and when to build. • Commercially literate: You can justify platform investment to VP / C-suite and translate business priorities into a roadmap.

🏖️ Benefits

• Health insurance • 401(k) matching • Flexible work hours • Paid time off • Remote work options

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