At a Glance
- Tasks: Solve real-world business problems using machine learning and lead a talented team.
- Company: Join a leading tech company focused on innovative eCommerce solutions.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and technical excellence.
- Why this job: Make a significant impact in the eCommerce space with cutting-edge ML technologies.
- Qualifications: Experience in machine learning, coding skills in C/C++ or Python, and leadership abilities.
The predicted salary is between 60000 - 80000 £ per year.
Responsibilities
- Partner with product teams and other engineers to solve Shops Ads business problems through ML.
- Play a critical role in setting the direction and goals for a sizable team, in terms of project impact, ML system design, and ML excellence.
- Re-evaluate the tradeoffs of already shipped features/ML systems, and drive large efforts across multiple teams to reduce technical debt, designing from first principles when appropriate.
- Lead a team from a technical perspective to develop ML best practices and influence engineering culture.
- Be a go-to person to elevate the most complex online/production performance and evaluation issues, requiring an in-depth knowledge of how the machine learning system interacts with surrounding systems.
- Suggest, collect and synthesize requirements and create an effective feature roadmap.
- Code deliverables that will tie the ML solutions developed to our ad delivery stack.
Minimum Qualifications
- Experience in one or more of the following areas: machine learning, recommendation systems, pattern recognition, data mining, artificial intelligence, or related technical field.
- Experience with developing machine learning models at scale from inception to business impact.
- Knowledge developing and debugging in C/C++ and Java, or experience with scripting languages such as Python, Perl, PHP, and/or shell scripts.
- Experience demonstrating technical leadership working with teams, owning projects, defining and setting technical direction for projects.
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
Preferred Qualifications
- Master's degree or PhD in Computer Science or a related technical field.
- Exposure to architectural patterns of large scale software applications.
Machine Learning Engineer - Core Ads Ecommerce employer: Meta Platforms, Inc.
As a Machine Learning Engineer at our dynamic eCommerce hub, you will thrive in a collaborative environment that champions innovation and technical excellence. We offer competitive benefits, a culture of continuous learning, and ample opportunities for professional growth, all while being part of a vibrant team dedicated to solving complex business challenges through cutting-edge machine learning solutions.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer - Core Ads Ecommerce
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's a GitHub repo or a personal website, let your work speak for itself and demonstrate your expertise in ML systems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past projects in detail. We want to see how you think and approach complex problems!
✨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 Machine Learning Engineer - Core Ads Ecommerce
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your experience with machine learning, recommendation systems, and any relevant projects you've worked on. We want to see how your skills align with our needs!
Showcase Your Projects:Include specific examples of machine learning models you've developed, especially those that had a tangible business impact. We love seeing real-world applications of your skills, so don’t hold back on the details!
Technical Skills Matter:Don’t forget to list your programming skills! Whether it's C/C++, Java, or Python, make sure we know what you’re comfortable with. If you’ve got experience debugging or developing in these languages, let us know!
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it gets into the right hands!
How to prepare for a job interview at Meta Platforms, Inc.
✨Know Your ML Stuff
Make sure you brush up on your machine learning concepts, especially those related to recommendation systems and data mining. Be ready to discuss your past projects and how they impacted the business. This shows you can connect technical skills with real-world applications.
✨Show Off Your Coding Skills
Since coding is a big part of this role, be prepared to demonstrate your proficiency in languages like C/C++ or Python. You might be asked to solve a problem on the spot, so practice coding challenges beforehand to keep your skills sharp.
✨Talk Teamwork and Leadership
This position requires technical leadership, so think of examples where you've led a team or influenced engineering culture. Share stories that highlight your ability to collaborate with product teams and drive projects forward, showcasing your leadership style.
✨Prepare for Technical Deep Dives
Expect to dive deep into technical discussions about ML systems and their interactions with other systems. Brush up on architectural patterns of large-scale applications and be ready to discuss how you would approach reducing technical debt in existing systems.
