At a Glance
- Tasks: Develop cutting-edge AI algorithms to enhance ad quality and user experience.
- Company: Join Meta, a leader in tech innovation and digital advertising.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Be part of a dynamic team driving long-term revenue growth through innovative solutions.
- Why this job: Make a real impact on how ads connect users and businesses globally.
- Qualifications: Experience in machine learning and software development, especially with Python or C++.
The predicted salary is between 80000 - 100000 £ 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
- Standardizing and optimizing quality treatment of ads across surfaces and page types
- Understanding user behavior 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 cross‑functional teams 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) to Non‑Purchaser (NP) user conversions from bad purchase experiences.
- Modeling: Enhance quality and drive long‑term revenue growth through modeling.
- Quality Science: Build the foundational end to end understanding for funnel quality signals to ensure the 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:
- 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:
- Experience in User Behaviour modeling, Long‑term Value optimization or Causal Learning
- Experience in Reinforcement Learning, GenAI, Large Language Models, etc.
- PhD in Artificial Intelligence (AI), computer science, related technical fields, or equivalent practical experience
- Experience in Ads, especially in auction theory and implementation (bidding, budgeting, targeting)
Industry: Internet
Staff Software Specialist - AI - Monetisation employer: Meta
Meta is an exceptional employer, offering a dynamic work culture that thrives on innovation and collaboration. As a Staff Software Specialist in AI - Monetisation, you will engage in meaningful projects that directly impact user experience and revenue growth across platforms like Facebook and Instagram. With a strong emphasis on employee development and cutting-edge technology, Meta provides unique opportunities for professional growth in a fast-paced environment, making it an ideal place for those looking to make a significant impact in the tech industry.
StudySmarter Expert Advice🤫
We think this is how you could land Staff Software Specialist - AI - Monetisation
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Meta or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Meta.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Meta.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Meta that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Staff Software Specialist - AI - Monetisation
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Meta.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Meta and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Meta
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Meta uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
