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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 programming with Python and Java, and experienced in deploying large-scale production machine learning systems.
Highest-signal resume keywords
Machine Learning Infrastructure DesignPython ProgrammingJava ProgrammingBig Data Processing FrameworksDistributed Systems
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 OptimizationFeature Generation PipelinesHigh-Performance Inference SystemsData Management SystemsScalable Model TrainingCode Correctness StandardsSystem Performance OptimizationAI Model ServingProduction-Ready Quality
Soft Skills
Problem-Solving Skills
Tools & Technologies
SparkFlinkRayTensorFlowPyTorchCaffe2Spark MLScikit-Learn
Certifications & Qualifications
Bachelor’s Degree in Technical FieldMaster’s Degree in Technical FieldPhD in Relevant Technical Field
Industry Keywords
Machine LearningDistributed SystemsBig Data ProcessingAI Model InferenceCloud Infrastructure
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 cloud infrastructure for scalable ML model training, evaluation, and inference
- Build data management systems for scalable data collection, labeling, processing, and evaluation
- Work closely with ML engineers to deploy models into production
- Use AI tools and high-velocity engineering workflows to design and ship scalable services
- Uphold 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 big data processing frameworks such as Spark, Flink, or Ray
- Proven track record of operating highly-available systems at significant scale
- Preferred: Master’s/PhD in a technical field such as computer science or equivalent industry experience
- Preferred: Experience working with ML Training platforms or optimizing AI model inference
- Preferred: Familiarity with ML frameworks such as TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks
Benefits
Comp & perks- Paid parental leave
- Comprehensive medical coverage
- Emotional and mental health support programs
- Compensation packages including equity in the form of RSUs