Software Engineer, ML Infrastructure (AI)

TL;DR

Software Engineer, ML Infrastructure (AI): Designing and optimizing large-scale ML infrastructure systems with an accent on AI training, inference, and data management. Focus on developing high-performance inference systems, building scalable model training platforms, and improving vector search algorithms.

Location: At Snap Inc. we practice a “default together” approach and expect our team members to **work in an office 4+ days per week**. This position is based in one of the following US cities: **Bellevue, Los Angeles, New York, Palo Alto, San Francisco, or Seattle**.

Salary: $209,000-$313,000 annually (Zone A - CA, WA, NYC).

Company

Snap Inc. is a technology company focused on improving communication and expression through its core products: hirify.global, Lens Studio, and Spectacles.

What you will do

• Design and optimize ML infrastructure systems for scale, reliability, and efficiency.
• Develop high-performance inference systems for fast AI model serving.
• Build scalable ML model training, evaluation, and inference infrastructure in the cloud.
• Create comprehensive data management systems for data collection, labeling, processing, and evaluation.
• Work on state-of-the-art vector search algorithms to enhance retrieval systems.
• Collaborate with ML engineers to deploy cutting-edge models into production.

Requirements

• **Strong programming skills in Python, Java, Scala, or C++**.
• Strong problem-solving skills with a focus on system performance, scalability, and efficiency.
• Good understanding of distributed systems and large-scale ML infrastructure.
• Experience with big data processing frameworks like Spark, Flink, or Ray.
• **Bachelor’s degree in Computer Science or equivalent experience**.
• **6+ years of post-Bachelor’s software development experience, or Master’s degree + 5+ years, or PhD + 2+ years**.

Nice to have

• Masters/PhD in a technical field or equivalent industry experience.
• Experience working with ML training platforms or optimizing AI model inference.
• Familiarity with ML frameworks such as TensorFlow, PyTorch, or Caffe2.

Culture & Benefits

• “Default Together” approach: **Work in an office 4+ days per week**.
• Comprehensive medical coverage, emotional and mental health support programs.
• Paid parental leave and compensation packages that include equity (RSUs).
• Commitment to diversity and belonging, as an equal opportunity employer.