Software Engineer, ML Infrastructure

SNAP/SNAP

. Design and optimize infrastructure systems for machine learning workloads at scale .

Posted 9/22/2026full-timeBellevue • Washington • United StatesMid-LevelSenior💰 $209,000 - $313,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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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 advanced models and improve system performance and efficiency.

Highest-signal resume keywords

Machine Learning Infrastructure DesignLarge-Scale Production SystemsPython ProgrammingBig Data Processing FrameworksDistributed Systems Understanding

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning SystemsInfrastructure OptimizationHigh-Performance Inference SystemsData Management SystemsVector Search AlgorithmsPythonJavaScalaC++Problem-Solving

Soft Skills

CollaborationProactive Learning

Tools & Technologies

SparkFlinkRayTensorFlowPyTorchCaffe2Spark MLScikit-learn

Industry Keywords

Machine LearningDistributed SystemsBig Data ProcessingAI Model ServingScalability

Tech Stack

Tools & technologies

CloudDistributed 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 comprehensive data management systems for scalable data collection, labeling, processing, and evaluation
Work on state-of-the-art vector search algorithms to improve retrieval-system precision, recall, and scalability
Collaborate with ML engineers to deploy cutting-edge models into production

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
Understanding of distributed systems and large-scale ML infrastructure components
Experience with big data processing frameworks such as Spark, Flink, or Ray
Proven track record operating highly available systems at significant scale
Ability to collaborate and work well with others
Ability to proactively learn new concepts and apply them at work
Preferred: Master’s/PhD in a technical field or equivalent industry experience
Preferred: Experience with ML training platforms or optimizing AI model inference
Preferred: Familiarity with 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
Default together approach with in-office work 4+ days per week