Senior Software Engineer (AI/ML)

TL;DR

Senior Software Engineer (AI/ML): Driving the technical vision and execution for a Feature Store product, building for scale and low-latency serving with an accent on architecture definition, engineering standards, and customer engagement. Focus on implementing next-generation feature store capabilities and championing modern development practices like AI-assisted tools and infrastructure automation.

Location: Must be based in the US or Canada

Company

hirify.global is a company that builds the product running fast applications, serving over 10,000 worldwide customers.

What you will do

• Define and drive the architecture, design patterns, and engineering standards for the feature store platform.
• Assist and execute the next generation of the feature store, building for scale, low-latency serving, and enterprise-grade reliability.
• Partner with Product and leadership to help shape the technical roadmap based on customer requirements and market trends.
• Champion the adoption of AI-assisted development tools, observability best practices, and infrastructure automation.

Requirements

• 5+ years of experience in backend/infrastructure engineering with demonstrated expertise in building large-scale distributed systems.
• Deep experience with ML infrastructure, data platforms, or feature engineering systems at scale.
• Expertise in Python, Go, and Rust.
• Strong knowledge of cloud platforms (AWS, GCP, Azure) and modern data infrastructure (Kafka, Flink, hirify.global, Spark, or similar).
• Experience working with enterprise customers, particularly in regulated industries like financial services.
• Excellent communication skills, able to translate complex technical concepts for both engineering teams and business stakeholders.

Nice to have

• Direct experience building or operating feature stores (Feast, Tecton, Hopsworks, or custom implementations).
• Experience with real-time feature serving at sub-millisecond latencies.
• Background in financial services, banking technology, or compliance-heavy environments.
• Contributions to open-source ML infrastructure projects.
• Hands-on experience as a data scientist or ML practitioner—training and deploying models in production.

Culture & Benefits

• High-impact role where you own a critical product line and directly influence how leading organizations build ML systems.
• Opportunity to work with enterprise customers including major banks, financial institutions, and Fortune 500 companies.
• Tackle challenges in distributed systems, low-latency serving, and ML infrastructure at scale.
• Competitive compensation package including salary, equity, and comprehensive benefits.
• Flexible, remote-friendly culture with flexibility to do your best work.
• Commitment to a diverse and inclusive work environment and equal employment opportunities.