At a Glance
- Tasks: Design and optimise ML infrastructure systems for Snapchat, enhancing AI training and recommendations.
- Company: Join Snap Inc, a leading tech company revolutionising communication through innovative products.
- Benefits: Enjoy competitive pay, health coverage, parental leave, and mental health support.
- Why this job: Make a real impact on millions of users while working with cutting-edge technology.
- Qualifications: Strong programming skills and experience in large-scale ML systems are essential.
- Other info: Dynamic office culture with a focus on collaboration and diversity.
The predicted salary is between 36000 - 60000 ÂŁ per year.
Snap Inc is a technology company. We believe the camera presents the greatest opportunity to improve the way people live and communicate. Snap contributes to human progress by empowering people to express themselves, live in the moment, learn about the world, and have fun together. The Company’s three core products are Snapchat, a visual messaging app that enhances your relationships with friends, family, and the world; Lens Studio, an augmented reality platform that powers AR across Snapchat and other services; and its AR glasses, Spectacles. Snap Engineering teams build fun and technically sophisticated products that reach hundreds of millions of Snapchatters around the world, every day. We’re deeply committed to the well-being of everyone in our global community, which is why our values are at the root of everything we do. We move fast, with precision, and always execute with privacy at the forefront.
You’ll play a critical role in scaling our ML Infrastructure, optimizing AI training and inference systems, and driving innovations that make Snapchat’s ranking and recommendation systems more efficient and impactful.
What you’ll do:
- Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
- Build and enhance feature generation pipelines that power real-time and batch ML models for content ranking and recommendations
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build infrastructure to perform scalable ML model training, evaluation, and inference in the cloud
- Develop high-performance inference systems to ensure fast and efficient AI model serving
- Build comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
- Work closely with ML engineers to deploy cutting-edge models into production
Knowledge, Skills & Abilities:
- Strong programming skills in Python, Java, Scala or C++
- Strong problem-solving skills with a focus on system performance, scalability, and efficiency
- Good understanding of distributed systems and the infrastructure components of large-scale ML
- Experience with big data processing frameworks such as Spark, Flink, or Ray
- Ability to collaborate and work well with others
- Proven track record of operating highly-available systems at significant scale
- Ability to proactively learn new concepts and apply them at work
Minimum Qualifications:
- Bachelor’s degree in a technical field such as computer science or equivalent experience
- Post-Bachelor’s software development experience; or Master’s degree in a technical field + post-grad software development experience; or PhD in a relevant technical field
- Experience building large scale production machine learning systems, distributed systems or big data processing
Preferred Qualifications:
- Masters/PhD in a technical field such as computer science or equivalent industry experience
- Experience working with ML Training platforms or optimizing AI model inference
- Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
If you have a disability or special need that requires accommodation, please don’t be shy and provide us some information.
Default Together Policy at Snap: At Snap Inc. we believe that being together in person helps us build our culture faster, reinforce our values, and serve our community, customers and partners better through dynamic collaboration. To reflect this, we practice a “default together” approach and expect our team members to work in an office 4+ days per week.
At Snap, we believe that having a team of diverse backgrounds and voices working together will enable us to create innovative products that improve the way people live and communicate. Snap is proud to be an equal opportunity employer, and committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, pregnancy, childbirth and breastfeeding, age, sexual orientation, military or veteran status, or any other protected classification, in accordance with applicable federal, state, and local laws. EOE, including disability/vets.
Our Benefits: Snap Inc. is its own community, so we’ve got your back! We do our best to make sure you and your loved ones have everything you need to be happy and healthy, on your own terms. Our benefits are built around your needs and include paid parental leave, comprehensive medical coverage, emotional and mental health support programs, and compensation packages that let you share in Snap’s long-term success!
Software Engineer, ML Infrastructure employer: Snap Inc.
Contact Detail:
Snap Inc. Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Software Engineer, ML Infrastructure
✨Tip Number 1
Network like a pro! Reach out to current or former Snap employees on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the technical interview! Brush up on your coding skills in Python, Java, or Scala. Practice common ML infrastructure problems and be ready to showcase your problem-solving skills.
✨Tip Number 3
Show your passion for Snap’s products! Familiarise yourself with Snapchat, Lens Studio, and Spectacles. Being able to discuss how you can contribute to these products will make you stand out.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Snap team!
We think you need these skills to ace Software Engineer, ML Infrastructure
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Software Engineer, ML Infrastructure role. Highlight your experience with machine learning systems and programming languages like Python or Java, as these are key to what we’re looking for.
Showcase Your Projects: Include any relevant projects or experiences that demonstrate your skills in building scalable ML infrastructure. We love seeing real-world applications of your work, so don’t hold back on sharing your achievements!
Be Clear and Concise: When writing your application, keep it clear and to the point. Use bullet points where possible to make it easy for us to see your qualifications and experiences at a glance. We appreciate straightforward communication!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Snap Inc.
✨Know Your Tech Inside Out
Make sure you brush up on your programming skills, especially in Python, Java, Scala, or C++. Be ready to discuss your experience with distributed systems and big data processing frameworks like Spark or Flink. The more you can demonstrate your technical prowess, the better!
✨Showcase Your Problem-Solving Skills
Prepare to tackle some system performance and scalability problems during the interview. Think of examples from your past work where you optimised systems or solved complex issues. This will show that you can think critically and apply your knowledge effectively.
✨Collaborate Like a Pro
Snap values teamwork, so be ready to discuss how you've worked with others in the past. Share specific instances where collaboration led to successful outcomes, especially in deploying machine learning models or building infrastructure. This will highlight your ability to fit into their culture.
✨Stay Current with ML Trends
Familiarise yourself with the latest trends in machine learning and AI model inference. Being able to discuss recent advancements or tools like TensorFlow or PyTorch will show your passion for the field and your commitment to continuous learning.