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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and optimizing infrastructure systems for machine learning workloads, with a strong focus on building scalable data management systems and high-performance inference systems. Proficient in collaborating with ML engineers to deploy models and ensure system reliability and efficiency.
Highest-signal resume keywords
Machine Learning Infrastructure DesignLarge-Scale Production SystemsPython ProgrammingBig Data Processing FrameworksDistributed Systems Understanding
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine Learning SystemsInfrastructure OptimizationData Management SystemsHigh-Performance Inference SystemsVector Search AlgorithmsPythonJavaScalaC++Big Data Processing
Soft Skills
Problem-SolvingCollaborationProactive Learning
Tools & Technologies
SparkFlinkRayTensorFlowPyTorchCaffe2Spark MLScikit-Learn
Industry Keywords
Machine LearningDistributed SystemsData ProcessingAI Model ServingData Quality Monitoring
Tech Stack
Tools & technologiesCloudDistributed SystemsJavaPythonPyTorchRayScalaScikit-LearnSparkTensorflowC++
About the role
Key responsibilities & impact- Design and optimize infrastructure systems for machine learning workloads at scale
- Drive reliability and efficiency improvements across Snapchat’s ML Infrastructure
- Develop high-performance inference systems for fast and efficient AI model serving
- Build cloud infrastructure for scalable ML model training, evaluation and inference
- Build data management systems for scalable data collection, labeling, processing and evaluation
- Work on vector search algorithms to improve retrieval precision, recall and scalability
- Work closely with ML engineers to deploy models into production
- Build foundational data platforms supporting offline model training and online feature serving
- Provide tools for data quality monitoring, feature management, lifecycle tracing and feature deprecation
- Continuously optimize storage and processing to sustain Snap’s ML growth
Requirements
What you’ll need- 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 plus 5+ years of post-graduate software development experience; or PhD in a relevant technical field plus 2+ years of post-graduate software development experience
- Experience building large-scale production machine learning systems, distributed systems or big data processing
- Strong programming skills in Python, Java, Scala or C++
- Strong problem-solving skills focused on system performance, scalability and efficiency
- Good understanding of distributed systems and infrastructure components of large-scale ML
- Experience with big data processing frameworks such as Spark, Flink or Ray
- Proven track record of operating highly available systems at significant scale
- Experience working with ML training platforms or optimizing AI model inference
- Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML or scikit-learn
- Ability to collaborate and work well with others
- Ability to proactively learn new concepts and apply them at work
Benefits
Comp & perks- Paid parental leave
- Comprehensive medical coverage
- Emotional and mental health support programs
- Compensation packages that let you share in Snap’s long-term success
- Equity in the form of RSUs
- Default Together approach with team members expected to work in an office 4+ days per week