Software Engineer, ML Infrastructure, Content Signal & Training Data, Level 4

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 Content Signal & Training Data infrastructure, developing new signals for content ranking and retrieval, optimizing training data pipelines, and driving innovations that make Snapchat’s ranking and recommendation systems more reliable, efficient, and impactful.

We’re looking for a Software Engineer, Content Signal & Training Data Infrastructure to join Snap Inc!

What you’ll do:

• Design and optimize systems for large-scale signal generation, indexing, serving, and applications

• Build and maintain content feature lifecycle management, including generation, storage, sourcing, monitoring, and deprecation of unused features

• Simplify the content feature development process by collaborating with ML data platform teams and improving tooling for generation, storage, and sourcing

• Optimize and monitor signal pipelines for reliability, latency, and scalability

• Build and maintain training data for new applications and ranking models, including experiments on long-term objectives such as user retention and creator affinity

• Collaborate with ML engineers to improve training workflows (feature engineering, preprocessing, model iterations, evaluation, and inference)

• Build training data monitoring and analysis tools with platform teams, including SQL-based analysis, feature importance, discrepancy detection, and anomaly detection

Knowledge, Skills & Abilities:

• Strong programming skills in Python, Java, Scala, or C++

• Strong problem-solving skills with a focus on system performance, data quality, and scalability

• Good understanding of distributed systems, data pipelines, and ML infrastructure

• Familiarity with feature engineering, signal pipelines, and model training workflows

• Proven track record of operating highly available and reliable infrastructure at scale

• Ability to proactively learn new concepts and apply them in a fast-paced environment

• Strong collaboration skills with ML engineers, data scientists, and infra teams

Minimum Qualifications:

• Bachelor’s degree in a technical field such as computer science or equivalent experience

• 2+ years of post-Bachelor’s software development experience; or Master’s degree in a technical field + 1+ years of post-grad software development experience; or PhD in a relevant technical field

• Experience building large-scale data or ML production systems, distributed systems, or big data processing

Preferred Qualifications:

• Masters/PhD in a technical field such as computer science or equivalent industry experience

• Experience with feature or training data pipelines

• Experience with big data processing frameworks such as Spark, Flink, Dataflow, or Ray

• Experience with search or recommendation systems

If you have a disability or special need that requires accommodation, please don’t be shy and provide us some