Staff Software Engineer (ML Infrastructure)

TL;DR

Staff Software Engineer (ML Infrastructure): Designing and optimizing large-scale machine learning infrastructure systems with an accent on embedding generation, feature storage, and training data compute. Focus on building high-performance, reliable distributed systems to enhance hirify.global’s ranking and recommendation capabilities at massive scale.

Location: Must be based in the US (Bellevue, Palo Alto, or Seattle). Hybrid role: requires office attendance 4+ days per week.

Company

hirify.global is a technology company focused on visual messaging and camera-based products that enhance human connection and expression.

What you will do

• Design and optimize infrastructure systems for machine learning workloads at scale.
• Develop high-performance embedding generation and batch inference systems.
• Build scalable data storage and compute systems to improve ML infrastructure efficiency.
• Integrate state-of-the-art ML data quality systems to ensure model performance.
• Develop comprehensive data management systems for collection, labeling, and evaluation.
• Collaborate with ML engineers to deploy cutting-edge models into production.

Requirements

• Must be based in the US and able to work from the office 4+ days per week.
• Bachelor’s degree in a technical field or equivalent experience.
• 9+ years of post-Bachelor’s software development experience (or 5+ years with Master’s, 2+ years with PhD).
• Strong programming skills in Python, Java, Scala, or C++.
• Proven track record of operating highly-available distributed systems at significant scale.
• Deep understanding of infrastructure components for large-scale machine learning.

Nice to have

• Experience with big data processing frameworks such as Spark, Flink, or Ray.
• Experience with large-scale feature stores or embedding systems.
• Familiarity with ML frameworks such as PyTorch or TensorFlow.

Culture & Benefits

• Comprehensive medical coverage and emotional/mental health support programs.
• Paid parental leave.
• Compensation packages including long-term success sharing.
• Commitment to diversity, equity, and inclusion.
• Dynamic, fast-paced environment with a focus on privacy and innovation.