Software Engineer, Platform
Greenlite AI
Distributed Systems
Software Engineer, ML Infrastructure – Content Signal and Training Data, Level 5
Snap Inc.
full-time
Posted on:
Location Type: Office
Location: San Francisco • California, Washington • 🇺🇸 United States
Visit company websiteSalary
💰 $209,000 - $313,000 per year
Job Level
JuniorMid-Level
Tech Stack
Distributed SystemsJavaPythonPyTorchRayScalaSparkSQLTensorflow
About the role
- 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
Requirements
- 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 + 5+ years; or PhD + 2+ years
- Experience building large-scale data or ML production systems, distributed systems, or big data processing systems
- Preferred: Masters/PhD, experience with feature platforms, logjoin optimization, training data systems, TensorFlow, PyTorch, Spark ML, signal pipelines, feature registries, retrieval systems, data quality monitoring
- Preferred: hands-on experience with Snap internal tech stacks such as Robusta, Hashi, Dataflow, Feature Registry, Mixer, Retrieval Service, logjoin, and dcoll
Benefits
- paid parental leave
- comprehensive medical coverage
- emotional and mental health support programs
- compensation packages that let you share in Snap’s long-term success
- this position is eligible for equity in the form of RSUs
ATS Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
PythonJavaScalaC++big data processingfeature engineeringsignal pipelinesmodel training workflowslogjoin optimizationdata quality
Soft skills
problem-solvingcollaborationproactive learning
