Track This Job
Add this job to your tracking list to:
- Monitor application status and updates
- Change status (Applied, Interview, Offer, etc.)
- Add personal notes and comments
- Set reminders for follow-ups
- Track your entire application journey
Save This Job
Add this job to your saved collection to:
- Access easily from your saved jobs dashboard
- Review job details later without searching again
- Compare with other saved opportunities
- Keep a collection of interesting positions
- Receive notifications about saved jobs before they expire
AI-Powered Job Summary
Get a concise overview of key job requirements, responsibilities, and qualifications in seconds.
Pro Tip: Use this feature to quickly decide if a job matches your skills before reading the full description.
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
Key Skills
Ranked by relevanceReady to apply?
Join AMISEQ and take your career to the next level!
Application takes less than 5 minutes

