Snap Inc is looking to scale its ML Infrastructure, optimize AI training and inference systems, and drive innovations that make Snapchat's ranking and recommendation systems more efficient and impactful.
Requirements
- 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
- Proven track record of operating highly-available systems at significant scale
- Experience building large scale production machine learning systems, distributed systems or big data processing
- Experience working with ML Training platforms or optimizing AI model inference
Responsibilities
- Design and optimize infrastructure systems for machine learning workloads at scale and drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
- 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 on state-of-the-art vector search algorithms to improve the precision, recall and scalability of our retrieval systems
- Work closely with ML engineers to deploy cutting-edge models into production
Other
- Ability to collaborate and work well with others
- Ability to proactively learn new concepts and apply them at work
- Bachelor’s degree in a technical field such as computer science or equivalent experience
- 6+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 5+ year of post-grad software development experience; or PhD in a relevant technical field+ 2+ years of post-grad software development experience
- Default together approach and expect our team members to work in an office 4+ days per week.
