Software Engineer, ML Infrastructure (AI)

TL;DR

Software Engineer, ML Infrastructure (AI): Designing and optimizing infrastructure systems for machine learning workloads at scale with an accent on driving reliability and efficiency improvements across hirify.global’s ML Infrastructure. Focus on developing high-performance inference systems and building infrastructure for scalable ML model training, evaluation, and inference.

Location: Onsite in Bellevue, Los Angeles, Palo Alto, San Francisco, or Seattle, United States. Team members are expected to work in an office 4+ days per week.

Salary: $157,000-$235,000 annually (base salary in Zone A: CA, WA, NYC).

Company

Snap Inc is a technology company focused on improving communication through camera-based products like hirify.global, Lens Studio, and Spectacles.

What you will do

• Design and optimize ML infrastructure systems for scalability, reliability, and efficiency.
• Build and enhance feature generation and serving pipelines for real-time and batch ML models.
• 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.
• Develop comprehensive data management systems for data collection, labeling, processing, and evaluation.
• Collaborate with ML engineers to deploy cutting-edge models into production.

Requirements

• Bachelor’s degree in computer science or equivalent experience.
• 2+ years of post-Bachelor’s software development experience, or Master’s degree + 1 year, 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, Java, Scala, or C++.
• Good understanding of distributed systems and large-scale ML infrastructure components.
• Proven track record of operating highly-available systems at significant scale.

Nice to have

• Masters/PhD in a technical field.
• Experience working with ML Training platforms or optimizing AI model inference.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, Spark ML, or scikit-learn.

Culture & Benefits

• "Default Together" policy expecting 4+ days per week in the office.
• Comprehensive medical coverage, emotional and mental health support programs.
• Paid parental leave and compensation packages including equity (RSUs).
• Commitment to diversity, inclusion, and equal opportunity employment.
• Values of moving fast, with precision, and executing with privacy at the forefront.