Machine Learning Engineer

This role focuses on building and running large-scale machine learning systems that power Client’s advertising platform, helping sellers optimize their ads while ensuring fast, reliable, production-ready ML services

What you’ll do day to day

• Work closely with data scientists, researchers, engineers, and product teams.
• Build systems that:
• Recommend where ads should appear
• Suggest which products to advertise
• Choose the right keywords, bids, and budgets
• Turn machine learning ideas into real, live systems used by millions.
• Build and manage:
• Data pipelines (getting data in the right shape)
• ML models (training and improving them)
• Deployment systems (getting models into production)
• Monitoring tools (making sure everything keeps working)
• Improve system speed so ads show quickly and reliably.
• Analyze results, run experiments, and explain insights in a way non-technical teams can understand.
• Monitor production systems and help fix issues if something breaks.

What kind of engineer they’re looking for

They want someone who:

• Can code well (Python, SQL, Java/Scala).
• Understands machine learning basics and how to apply them in real products.
• Has experience putting ML models into production, not just building them in notebooks.
• Knows how to work with large-scale data (Spark, big databases).
• Understands how ML systems run at scale (cloud, GPUs, autoscaling, monitoring).
• Can debug problems and communicate clearly with different teams.

Bonus points if you’ve worked with:

• Deep learning / LLMs
• Monitoring tools like Grafana
• Dashboards and visualization tools