Snap Inc.
Software Engineer, ML Infrastructure, Content Signal & Training Data, Level 4
Snap Inc., New York, New York, us, 10261
Software Engineer, ML Infrastructure, Content Signal & Training Data, Level 4
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Software Engineer, ML Infrastructure, Content Signal & Training Data, Level 4
role at
Snap Inc.
Snap Inc. is a technology company that empowers people to express themselves, live in the moment, and learn about the world. Its core products include Snapchat, Lens Studio, and Spectacles.
Snap Engineering teams build fun and technically sophisticated products. We’re committed to well‑being, speed, precision, and privacy.
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.
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 experience; or PhD in a relevant 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.
We are an equal‑opportunity employer and consider qualified applicants with criminal histories in a manner consistent with applicable law.
Compensation In the United States, work locations are assigned a pay zone. The starting pay is determined based on skills, experience, qualifications, work location, and market conditions. The ranges are:
Zone A (CA, WA, NYC): $157,000‑$235,000 annually.
Zone B: $149,000‑$223,000 annually.
Zone C: $133,000‑$200,000 annually.
This position is eligible for equity in the form of RSUs.
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Software Engineer, ML Infrastructure, Content Signal & Training Data, Level 4
role at
Snap Inc.
Snap Inc. is a technology company that empowers people to express themselves, live in the moment, and learn about the world. Its core products include Snapchat, Lens Studio, and Spectacles.
Snap Engineering teams build fun and technically sophisticated products. We’re committed to well‑being, speed, precision, and privacy.
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.
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 experience; or PhD in a relevant 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.
We are an equal‑opportunity employer and consider qualified applicants with criminal histories in a manner consistent with applicable law.
Compensation In the United States, work locations are assigned a pay zone. The starting pay is determined based on skills, experience, qualifications, work location, and market conditions. The ranges are:
Zone A (CA, WA, NYC): $157,000‑$235,000 annually.
Zone B: $149,000‑$223,000 annually.
Zone C: $133,000‑$200,000 annually.
This position is eligible for equity in the form of RSUs.
#J-18808-Ljbffr