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Join our dynamic team working on a cutting-edge advertising platform that reaches millions of users globally. As a Machine Learning Engineer, you’ll contribute to the design and development of scalable, high-performance ML pipelines and infrastructure. You'll collaborate with top-tier engineers and researchers to bring real-world impact through applied AI at scale.
🔍 What You’ll Be Doing
Develop and maintain scalable, low-latency ML pipelines and platforms
Build and optimize models using real-time and batch processing for billions of predictions daily
Collaborate with Data Scientists and MLOps teams on model lifecycle — from training to deployment and monitoring
Create proof-of-concept prototypes, experiment with new platforms, and support continuous integration and delivery
Streamline testing (unit, integration, stress), versioning, and automation of ML solutions
Research and apply the latest technologies in ML infrastructure
If you're experienced — you'll also get a chance to lead projects and mentor others
✅ What You Need to Succeed
5+ years of experience in machine learning or data science roles
Strong Python skills (incl. pandas
, scikit-learn
) and knowledge of SQL (preferably Snowflake)
Experience with ML libraries/frameworks: TensorFlow, PyTorch, Scikit-learn, PySpark
Strong grasp of data analysis, statistics, and model evaluation
Good understanding of CI/CD, version control (Git), and software engineering practices
Ability to communicate technical insights to product teams and stakeholders
Openness to learn and work in a cloud-based environment
⭐ Bonus Points for
Experience with advertising, recommender systems, or RTB platforms
Hands-on with AWS ML tools (e.g. SageMaker, Airflow), Snowflake, Redis, Aerospike
MLOps & infrastructure experience: Docker, Kubernetes, Terraform, GitHub Actions, Prometheus, Grafana
Previous technical leadership or mentoring experience
Experience deploying ML models to production environments
Net per hour - B2B
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