Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Develop cutting-edge AI algorithms and systems to enhance ad quality across platforms.
- Company: Join Meta, a leader in tech innovation and user engagement.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a real impact on how users interact with ads and drive long-term revenue.
- Qualifications: Bachelor's in AI or computer science; experience in machine learning and algorithm development.
- Other info: Dynamic team environment with significant career advancement potential.
The predicted salary is between 60000 - 84000 ÂŁ per year.
Ads is the largest revenue generator at Meta and Ads Quality represents around 20% of total revenues which are used to generate long term ads and organic engagement. Core Ads Quality is a unique team jointly optimizing for both quality and revenue, aiming at making this investment more revenue/quality trade‑off efficient and generate long term revenue growth through user learning. Among others, Core Ads Quality focuses on:
- Finding the right trade‑off between short and long term revenues
- Standardising and optimising quality treatment of ads across surfaces and page types
- Understanding user behaviour with respect to ads quality
- Building a solid infrastructure around signals, labels and quality metrics
We work at the intersection of Ads, Machine Learning and User Behaviour understanding. The nature of our work is very analytical, involving collaboration with our Data Scientist and a heavy focus on not only understanding “what” but also “why”. Despite having been created a couple of years ago, the Ads Quality space at Meta is still nascent and full of unexploited opportunities. The org is further structured into the following teams/sub‑pillars:
- Integrity & Efficiency: Proactively cover long‑term revenue risks from advertiser friction while supporting XI with delivery expertise.
- Ads Conversion Familiarity: Accelerate Non‑Purchaser (NP) ➜ Purchaser (P) transition by increasing familiarity of ads for users who don’t interact with ads frequently.
- Post‑Click Quality: Stop Purchaser (P) ➜ Non purchaser (NP) user conversions from bad purchase experiences.
- Modelling: Enhance quality and drive long‑term revenue growth through modelling.
- Quality Science: Build the foundational end‑to‑end understanding for funnel quality signals to ensure its efficiency, health and coverage.
The team has consistently hit their goals and delivered XXXM$ in incremental long‑term revenue for Meta while ensuring high ads quality.
Responsibilities
- Work on meaningful technical (ML and infra) problems at Meta’s scale affecting multiple surfaces (Facebook, Instagram, Threads,...)
- Fundamentally change how decisions are made across the business when investing in ads quality
- Develop novel, accurate AI algorithms and advanced systems for large‑scale applications
- Define long‑term plans and lead teams on executing them
- Improve the experience of users interacting with ads and help the company mission to establish valuable connections between users and businesses
- Lead projects with clear top‑line metric impact
- Ensure Ads Quality is at the forefront of AI technologies
Minimum Qualifications
- Bachelor in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience
- Experience in bringing research results into production
- Experience in training, fine‑tuning, and/or experimenting with foundation models beyond black‑box use
- Experience developing machine learning algorithms or machine learning infrastructure in Python, PyTorch, and/or C/C++
- Track record delivering successful products with large scale impact
Preferred Qualifications
- PhD in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience
- Experience in Reinforcement Learning, GenAI, Large Language Models, etc.
- Experience in Ads, especially in auction theory and implementation (bidding, budgeting, targeting)
- Experience in User Behaviour modelling, Long‑term Value optimization or Causal Learning
Industry Internet
Staff Software Specialist - AI/ML - Monetisation employer: Meta
Contact Detail:
Meta Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Software Specialist - AI/ML - Monetisation
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at Meta or similar companies. Use LinkedIn to connect and don’t be shy about asking for informational chats – you never know where a conversation might lead!
✨Tip Number 2
Prepare for interviews by diving deep into AI/ML topics relevant to the role. Brush up on your knowledge of ads quality and user behaviour. Practise explaining complex concepts simply; it shows you really understand your stuff!
✨Tip Number 3
Showcase your projects! Whether it's through a portfolio or GitHub, let your work speak for itself. Highlight any experience with machine learning algorithms or infrastructure that aligns with the job description.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Staff Software Specialist - AI/ML - Monetisation
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Staff Software Specialist role. Highlight your experience in AI, ML, and any relevant projects you've worked on that demonstrate your ability to tackle large-scale problems.
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Explain why you're excited about working at Meta and how your background makes you a perfect fit for the Ads Quality team.
Showcase Your Technical Skills: Don’t forget to include specific examples of your technical expertise, especially in Python, PyTorch, or C/C++. We want to see how you've applied these skills in real-world scenarios, so be detailed!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands and shows us you’re serious about joining our team!
How to prepare for a job interview at Meta
✨Know Your Stuff
Make sure you brush up on your knowledge of AI and machine learning, especially as it relates to ads quality. Be ready to discuss your experience with Python, PyTorch, and any relevant algorithms you've worked on. This is your chance to show how your skills can directly impact Meta's goals.
✨Understand the Business
Familiarise yourself with how Ads Quality fits into Meta's overall strategy. Knowing how your role can influence long-term revenue growth and user engagement will help you articulate your value during the interview. Think about how you can contribute to optimising the trade-off between quality and revenue.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions. Prepare to explain your past projects, particularly how you've brought research into production. Be ready to tackle questions on reinforcement learning and user behaviour modelling, as these are key areas for the role.
✨Show Your Collaborative Spirit
Since this role involves working closely with data scientists and other teams, highlight your teamwork skills. Share examples of how you've successfully collaborated on projects in the past, especially those that required cross-functional communication and problem-solving.
