Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5

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 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!

• 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

• Develop infrastructure for training data pipelines, including logjoin optimization, streaming logjoin, data sampling, data shuffling, and window tuning

• 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 Bento and data infra teams, including SQL-based analysis, feature importance, discrepancy detection, and anomaly detection

• Strong programming skills in Python, Java, Scala, or C++
  Strong problem-solving skills with a focus on system performance, data quality, and scalability

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

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

• 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

• 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+ years of post-grad software development experience; or PhD in a relevant technical field + 2+ years of post-grad software development experience

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

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

• Experience with feature platforms, logjoin optimization, and training data systems

• Familiarity with ML frameworks such as TensorFlow, PyTorch, or Spark ML

• Experience with signal pipelines, feature registries, retrieval systems, and data quality monitoring

• Hands-on experience with Snap’s internal tech stacks such as Robusta, Hashi, Dataflow, Feature Registry, Mixer, Retrieval Service, logjoin, and dcoll

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.

We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, where applicable).

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!

Compensation

In the United States, work locations are assigned a pay zone which determines the salary range for the position. The successful candidate’s starting pay will be determined based on job-related skills, experience, qualifications, work location, and market conditions. The starting pay may be negotiable within the salary range for the position. These pay zones may be modified in the future.

Zone A (CA, WA, NYC):

Zone B:

Zone C:

This position is eligible for equity in the form of RSUs.