Ml Infra Engineer (Ai)

TL;DR

Machine Learning Infrastructure Engineer (AI/ML): Designing and building scalable, reliable, and secure services for ML model training, experimentation, serving, and LLM applications with an accent on MLOps maturity and improving ML development velocity. Focus on creating seamless end-to-end experiences for ML engineers, solving complex technical and product challenges across diverse systems.

Location: Onsite in New York, South San Francisco HQ, or Seattle, USA. Must be comfortable working with hirify.global teams across the US and Canada.

Salary: $156,800–$235,200 (annual US base salary range).

Company

hirify.global is a financial infrastructure platform enabling millions of businesses, from startups to large enterprises, to accept payments, grow revenue, and accelerate new business opportunities.

What you will do

• Design and build scalable, reliable, and secure services for ML model training, experimentation, serving, and LLM applications across multiple regions.
• Create services and libraries that enable ML engineers to seamlessly transition from experimentation to production across hirify.global’s systems.
• Work directly with product teams and ML engineers to improve their day-to-day productivity.
• Take ownership of and find solutions for technical and product challenges by working with a diverse set of systems, processes, and technologies.

Requirements

• 2+ years of professional full time software development experience with a solid background on service oriented architecture and large-scale distributed systems.
• Experience working through the full life cycle of software development, from design and implementation to testing, deployment, and operations.
• Experience working on production ML platforms, MLOps solutions, or building LLM applications.
• Experience running operations for high availability, low latency systems.
• Experience partnering with other teams to drive business outcomes.
• A strong sense of pragmatism in technical problem-solving.

Nice to have

• Experience building and shipping production AI agents.
• Familiarity with LLMs and LLM Frameworks.
• Experience training and shipping machine learning models to production to solve critical business problems.

Culture & Benefits

• Contribute to increasing the GDP of the internet by building foundational infrastructure.
• Work on critical systems processing over $1T in payments volume per year.
• Accelerate the adoption of AI/ML across all parts of the company.
• Opportunity to do impactful work in a fast-evolving field of machine learning.
• Engage with complex, diverse systems and technologies.