Software Engineer, ML Infrastructure, Content Signal & Training Data Infrastructure, Level 5
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Snap Engineering teams build scientifically rigorous products reaching hundreds of millions of users daily. We’re looking for a Software Engineer to scale Content Signal & Training Data infrastructure, develop new signals for ranking and retrieval, optimize training data pipelines, and drive innovations that improve the reliability, efficiency, and impact of Snapchat’s ranking and recommendation systems.
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
- 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
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 scalabilityDeep understanding of distributed systems, data pipelines, and ML infrastructureExperience with big data processing frameworks such as Spark, Flink, Dataflow, or RayFamiliarity with feature engineering, signal pipelines, and model training workflows; proven track record of operating highly available and reliable infrastructure at scaleAbility to proactively learn new concepts and apply them in a fast-paced environmentStrong collaboration skills with ML engineers, data scientists, and infra teamsMinimum Qualifications
Bachelor’s degree in a technical field or equivalent experience6+ years of post-Bachelor’s software development experience; or Master’s degree + 5+ years; or PhD + 2+ yearsExperience building large-scale data or ML production systems, distributed systems, or big data processingPreferred Qualifications
Masters / PhD in a technical field or equivalent industry experienceExperience with feature platforms, logjoin optimization, and training data systemsFamiliarity with ML frameworks such as TensorFlow, PyTorch, or Spark MLExperience with signal pipelines, feature registries, retrieval systems, and data quality monitoringHands-on experience with Snap’s internal tech stacks such as Robusta, Hashi, Dataflow, Feature Registry, Mixer, Retrieval Service, logjoin, and dcollIf 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 : we expect team members to work in an office 4+ days per week to foster culture and collaboration.
Equal Opportunity Employer : Snap Inc. is an equal opportunity employer and is committed to providing employment opportunities regardless of race, religious creed, color, national origin, ancestry, physical or 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 laws. EOE, including disability / vets. We will consider qualified applicants with criminal histories as allowed by law (e.g., San Francisco Fair Chance Ordinance, Los Angeles Fair Chance Initiative for Hiring, where applicable).
Our Benefits : Snap offers benefits designed to support you and your loved ones, including paid parental leave, comprehensive medical coverage, mental health support programs, and compensation packages that enable shared long-term success.
Compensation : In the United States, starting pay is determined by various factors including skills, experience, location, and market conditions, and may be negotiable within the applicable range. Salary ranges vary by location and are subject to change. This position is eligible for equity in the form of RSUs.
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