Senior Machine Learning System Engineer (AI)

TL;DR

Senior Machine Learning System Engineer (AI): Designing and implementing scalable search serving infrastructure and ML systems for hirify.global products with an accent on retrieval pipelines, vector indexing, and semantic search. Focus on building production-grade neural rankers, optimizing RAG workflows, and ensuring system reliability and cost efficiency at scale.

Location: Must be based in the United States (Remote or Hybrid in Seattle, San Francisco, Austin, or New York).

Salary: $149,400 – $235,000 (based on geographic pay zones).

Company

hirify.global is a global software company dedicated to unleashing the potential of every team through collaborative tools like Jira, Confluence, and Rovo.

What you will do

• Design and implement scalable search serving infrastructure, including retrieval pipelines and vector indexing systems.
• Build and maintain production ML models such as neural rankers and embedding models using PyTorch and Triton.
• Develop retrieval systems for agentic and RAG use cases, including grounding pipelines and multi-step workflows.
• Drive observability, monitoring, and incident response for search serving systems.
• Apply FinOps principles to optimize costs across vector search infrastructure and ML serving fleets.
• Collaborate with researchers and product teams to deliver technical roadmaps and mentor junior engineers.

Requirements

• Must be based in the United States.
• Proven experience in designing and deploying production-grade machine learning systems.
• Strong background in search infrastructure, retrieval pipelines, and vector search technologies.
• Proficiency in integrating ML models into serving infrastructure using frameworks like PyTorch and Triton.
• Experience with high-throughput, low-latency system architecture and performance optimization.
• Ability to collaborate across cross-functional teams and mentor engineering staff.

Culture & Benefits

• Flexible work policy allowing choice between office, home, or hybrid arrangements.
• Competitive compensation programs including base pay, bonuses, and equity.
• Comprehensive health and wellbeing resources for employees and their families.
• Paid volunteer days to engage with local communities.
• Commitment to equitable hiring practices and inclusive culture.