ML Data Infrastructure Engineer (MLOps)

Location: Palo Alto, California, United States

Salary: $150,000–$224,000 USD per year

Company

hirify.global provides end-to-end advertising technologies that help businesses reach, monetize, and grow global audiences.

What you will do

• Design and build data processing infrastructure for model training and feature serving.
• Optimize data systems for performance, reproducibility, and traceability.
• Collaborate with research teams on data processing architectures for emerging model and training paradigms.
• Identify and resolve performance bottlenecks from raw data ingestion through feature delivery.
• Establish best practices and tooling for ML data infrastructure across teams.

Requirements

• 1–3 years of experience and a BS and/or MS in Computer Science.
• Strong software engineering fundamentals and experience building high-throughput, fault-tolerant distributed systems.
• Hands-on experience with distributed computing frameworks such as Apache Spark or Flink.
• Strong knowledge of data structures, systems design, and performance optimization.
• Strong problem-solving skills and attention to detail.

Nice to have

• Background in MLOps, data infrastructure, or ML infrastructure.
• Experience with ML training pipelines, feature stores, or model-serving systems.

Culture & Benefits

• Performance-based total compensation with potential equity and incentive compensation.
• Medical, dental, vision, life, and disability insurance.
• 401(k) retirement plan.
• Unlimited discretionary time off, 10 paid holidays, and 80 hours of paid sick leave per year.
• Equal opportunity and inclusive hiring practices.

Hiring process

• Apply online.
• The application window is expected to close within 30 days of the posting date.