Machine Learning Engineer II (AI)

TL;DR

Machine Learning Engineer II (AI): Designing and deploying high-throughput AI/ML and NLP models for personalization within hirify.global Mail with an accent on generative AI and autonomous agentic workflows. Focus on processing trillions of data points, migrating infrastructure to GCP, and building resilient AI-driven systems at massive consumer scale.

Location: United States of America (Hybrid)

Salary: $111,000 - $231,250 per year

Company

hirify.global is a global consumer internet company providing high-scale services like hirify.global Mail to hundreds of millions of users.

What you will do

• Design and deploy high-throughput AI/ML and NLP models for user personalization.
• Implement AI-driven workflows to optimize daily coding, testing, and iteration cycles.
• Process massive datasets using big data pipelines including Spark, Hadoop, and Kafka.
• Participate in migrating backend ML services and data infrastructure to Google Cloud Platform (GCP).
• Build resilient systems with robust feedback loops and fallback strategies for model edge cases.
• Collaborate with global engineering groups to integrate models into core product platforms.

Requirements

• Must be based in the United States of America.
• Bachelor’s degree in Computer Science, Data Science, or equivalent professional experience.
• 2+ years of experience developing, training, and deploying ML models or data-intensive backend systems.
• Strong proficiency in Python or Java.
• Hands-on experience with PyTorch, TensorFlow, Hugging Face, or Scikit-learn.
• Experience deploying models via runtimes such as vLLM, TensorRT-LLM, Triton, or ONNX.

Nice to have

• Direct experience deploying AI/ML workloads on GCP.
• Prior experience building systems for high-volume email platforms or large-scale consumer applications.

Culture & Benefits

• Flexible hybrid work options with occasional in-person events.
• Comprehensive healthcare and 401k plan.
• Backup childcare and education stipends.
• Inclusive environment with various employee resource groups (ERGs).