We are looking for MLOps Engineer to work remotely on a data projects that form a RTB exchange. We process over 10M requests/s and all teams constantly face with high volume, low latency and geo-distributed challenges.

We value technical excellence and you will have both resources and time to deliver world-class code.

This is a 100% remote position, for qualified candidates we help with visa and relocation to Wrocław, Poland.

You will be working with team members in NYC and Poland.

Salary range for this role: B2B: 24000 – 30000 PLN/month, UoP: 20000 – 25000 PLN/month, we can pay in PLN, EUR or USD.

We are happy to negotiate higher compensation if you are an ideal candidate.

In this role you will be working on the conception, design, development, testing, and deployment of real-world applications of models & data that impact billions of dollars of marketing spend.

We are seeking an experienced MLOps Engineer to ensure that the ML models developed by our Data Science team are successfully trained and deployed at our scale.

If you think you are a good fit even though you don’t meet all requirements – please apply, we are currently filling multiple roles and will do our best to find the best match.

Role Details

• Design and develop data pipelines and infrastructure to ensure our models have up-to-date models
• Train and experiment with models at scale using Spark, AWS/Sagemaker or DataBricks
• Deploy and serve models to achieve best quality and lowest latency
• Use workflow orchestration to ensure that our ML pipelines run smoothly
• Stay up to date with new frameworks and techniques, always look out to improve our tech
• Monitor models running in production
• A/B Testing and monitoring of new models
• Work on low latency feature stores

Key Requirements

• Min 5 years of practical experience with end-to-end ML systems as MLOps or similar role (Data Enginner, Platform Engineer, etc)
• Strong software engineering experience and skills: Python and additionally Scala
• Experience with Linux, Docker and Kubernetes
• Spark, AWS/Sagemaker, TFX (optional)
• Familiarity with KubeFlow, Airflow, Argo or similar system
• Familiarity with Tensorflow, Keras or similar frameworks

Bonus Experience

• Real Time Bidding (RTB), AdTech, High Frequency Trading (HFT) experience
• Distributed model training