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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 ML model training and inference systems. Proficient in programming with Python and Java, and experienced in deploying large-scale production machine learning systems.
Highest-signal resume keywords
Machine Learning Infrastructure DesignPython ProgrammingJava ProgrammingDistributed Systems ExperienceML Model Training and Inference Optimization
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 SystemsDistributed SystemsBig Data ProcessingHigh-Performance Inference SystemsFeature Generation PipelinesData Management SystemsAI Model ServingCode Correctness StandardsSystem Performance OptimizationScalability and Efficiency
Soft Skills
Problem-SolvingCollaborationAdaptabilityProactive Learning
Tools & Technologies
SparkFlinkRayTensorFlowPyTorchCaffe2Spark MLScikit-Learn
Industry Keywords
Cloud InfrastructureAI ToolsProduction-Ready QualityMachine Learning WorkloadsData Collection and Processing
Tech Stack
Tools & technologiesCloudDistributed SystemsJavaPythonPyTorchRayScikit-LearnSparkTensorflow
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
- Build and enhance feature generation and serving pipelines for online inferencing and offline training data generation
- Develop high-performance inference systems for fast and efficient AI model serving
- Build infrastructure for scalable ML model training, evaluation, and inference in the cloud
- Build data management systems for scalable data collection, labeling, processing, and evaluation
- Work closely with ML engineers to deploy cutting-edge models into production
- Use AI tools and high-velocity engineering workflows to design and ship scalable services
- Uphold rigorous standards for code correctness, security, and production-ready quality
Requirements
What you’ll need- 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+ year of post-grad software development experience; or PhD in a relevant technical field
- Experience building large scale production machine learning systems, distributed systems or big data processing
- Strong programming skills in Python and Java
- 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 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 TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
- Ability to collaborate and work well with others
- Ability to proactively learn new concepts and apply them at work
- Adaptability in learning and applying evolving AI systems and tools
Benefits
Comp & perks- Paid parental leave
- Comprehensive medical coverage
- Emotional and mental health support programs
- Compensation packages including equity in the form of RSUs