Software Engineer (ML Infrastructure/Core Inference)

Location: Bellevue, Los Angeles, or Palo Alto, United States; office work is expected 4+ days per week under the default-together policy.

Base salary: $133,000–$235,000 annually, depending on pay zone, skills, experience, qualifications, work location, and market conditions. The position is also eligible for RSUs.

Company

hirify.global is a technology company operating hirify.globalchat, Specs, Bitmoji, Saturn, and other digital services.

What you will do

• Build and operate machine learning infrastructure for personalized experiences across Discover, Stories, Spotlight, and other products.
• Optimize, export, and prepare models for efficient production use across training and inference workflows.
• Own hosting and serving infrastructure for recommendation models, embedding-generation models, and self-hosted large language models.
• Develop LLM fine-tuning, reinforcement learning infrastructure, serving, and inference optimization capabilities.
• Provide ranking and model-serving infrastructure for Ads, Content, Growth, Lenses, Security, My AI, and other product teams.
• Operate inference components for highly available, large-scale production machine learning systems.

Requirements

• Strong programming skills in Python and Java.
• Strong problem-solving skills focused on system performance, scalability, and efficiency.
• Understanding of distributed systems and large-scale machine learning infrastructure.
• Experience with big data processing frameworks such as Spark, Flink, or Ray.
• Bachelor’s degree in a technical field or equivalent experience, plus 2+ years of post-Bachelor’s software development experience; alternative Master’s and PhD pathways are accepted.
• Experience building large-scale production machine learning systems, distributed systems, or big data processing solutions.

Nice to have

• Master’s or PhD in a technical field such as computer science.
• Experience with ML training platforms or AI model inference optimization.
• Familiarity with TensorFlow, PyTorch, Caffe2, Spark ML, scikit-learn, or related frameworks.

Culture & Benefits

• In-person collaboration through the default-together work model.
• Paid parental leave.
• Comprehensive medical coverage.
• Emotional and mental health support programs.
• Equity compensation through RSUs and benefits designed to support employees and their families.