MLops Engineer

Seedtag; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Home office setup budget

Paid trips to HQ in Madrid

MacBook Pro M3

Learning platform

Language classes

Team offsites

Job summary

Seedtag ищет MLOps Engineer для масштабирования Liz, нашего контекстного AI, и обеспечения низкой задержки развёртывания моделей на глобальном уровне.

Ищем кандидата с 2–4 годами опыта в продакшн ML, сильным Python, опытом Kubernetes, CI/CD и мониторингом. У вас будет тесное взаимодействие с Data, Platform и Backend командами.

Условия — 100% удаленная или гибридная работа, удалённые контракты в нескольких странах Европы и поддержка обучения. MacBook Pro и бюджет на рабочее место — часть пакета.

Qualifications

• Опыт 2–4 года в продакшн ML системах.
• Глубокие знания Python, API-разработка и асинхронное программирование.
• Опыт в MLOps: CI/CD, версионирование моделей, мониторинг и воспроизводимость.

Responsibilities

• Развертывание и поддержка ML-моделей в продакшн, обеспечение latency- и reliability.
• Построение и улучшение пайплайнов данных для обучения, валидации и анализа производительности.
• Реализация мониторинга, дашбордов, drift-детекции и alerting.
• Улучшение CI/CD, версионирования моделей и инфраструктурной автоматизации.
• Оптимизация производительности и затрат на сервисы ML.
• Разработка внутренних автоматизаций и интеграций.
• Сотрудничество с командами Data, Platform и Backend.

Skills

Python

API development

Asynchronous programming

Testing

Clean architecture

Troubleshooting

Autonomous work

Tools

Kubernetes

Terraform

MLflow

Weights & Biases

Prometheus

Grafana

Kafka

Redis

Bigtable

MongoDB

Vertex AI

Job description

Описание: We’re looking for an MLOps Engineer to join our tech team and help build the future of neuro-contextual advertising at global scale. At Seedtag, our mission is to transform advertising by proving that effectiveness and user privacy can truly coexist. As the leading Neuro-Contextual Advertising Company, we combine Artificial Intelligence, Natural Language Processing, Computer Vision, and neuroscience to understand not only what content is about, but how it makes people feel and what they intend to do next. Our proprietary AI, Liz, enables brands to connect with audiences across the open web and Connected TV without cookies or user tracking. Founded in 2014 by two ex-Googlers, Seedtag has grown to 500+ Seedtaggers in 17 countries, backed by €250M in funding, and operates today as a global ad-tech leader. If you enjoy solving complex engineering challenges and building AI-driven systems at scale, you’ll feel right at home here.

Our Challenge: As our MLOps Engineer, you will help scale and maintain the infrastructure behind Liz, Seedtag's contextual AI, ensuring reliable, efficient, and low-latency ML model deployment across the open web and CTV.

Задачи:

• ML Model Deployment: Deploy, maintain, and optimise ML models in production, ensuring performance, reliability, and latency standards.
• Data Pipelines: Build and improve pipelines for dataset generation, model training, validation, and performance analysis.
• Model Observability: Implement monitoring, dashboards, drift detection, and alerting to ensure model quality and stability.
• MLOps Infrastructure: Improve CI/CD pipelines, model versioning, reproducibility, and infrastructure automation.
• Performance & Cost Optimisation: Identify opportunities to reduce serving costs and improve efficiency without compromising model quality.
• AI Automation: Develop internal automations and agentic integrations to streamline ML workflows.
• Cross-Functional Collaboration: Work closely with Data, Platform, and Backend teams to troubleshoot production issues and improve ML systems.

Our Core Values

Outcome over Output. We measure success by impact and value, not by volume of features or lines of code. Failure Is Allowed, Learning Is a Must. Experimentation is key to innovation. We test early, iterate often, and learn fast. We Are All Scouts. We take ownership and leave things better than we found them. We Are Data-Driven. Data informs our decisions and helps us continuously improve our systems and results.

Tech Stack

You’ll work with the technologies powering LizCore, our contextual AI infrastructure, supporting real-time ML model serving across the open web and CTV. Our stack includes:

• Languages: Python, Go.
• Cloud & Infrastructure: GCP, Vertex AI, Kubernetes, Terraform.
• MLOps & Monitoring: MLflow, Weights & Biases, Evidently, Prometheus, Grafana.
• Data & Messaging: Kafka, Redis, Bigtable, MongoDB.
• AI & Machine Learning: NLP, embeddings, ranking models, MCP, agentic workflows.
• Engineering Practices: CI/CD, model versioning, automated testing, reproducibility.

Требования:

• 2–4 years of experience building, deploying, and maintaining ML systems in production.
• Strong Python skills, including APIs, asynchronous programming, testing, and clean architecture.
• Hands‑on experience with ML model development and production deployment.
• Solid understanding of MLOps practices, including CI/CD, model versioning, reproducibility, and monitoring.
• Experience with ML observability, including performance metrics, dashboards, and alerting.
• Knowledge of distributed systems, microservices, Kubernetes, and cloud infrastructure.
• Strong troubleshooting skills across models, data pipelines, APIs, and infrastructure.
• Proactive, curious, and autonomous, with the ability to own technical components end to end.

Условия:

A key moment of growth with real ownership and global impact.

• Flexible work model with 100% remote or hybrid options.
• (Remote contracts available in Spain, Italy, UK, Belgium, Netherlands, France, and Germany.)
• Continuous learning through a learning platform and optional language classes.
• A supportive, trust-based culture that values well-being.
• Team activities, offsites, and opportunities to connect beyond work.
• Home office setup budget up to €1,000.
• Paid trips to our HQ in Madrid.
• MacBook Pro M3.

Ready to Join the Seedtag Adventure?

At Seedtag, we create an environment where everyone can thrive.

If you need accommodations during the hiring process, let us know and we’ll ensure a positive experience.