Staff Software and ML Engineer (AI/ML)

Location: Redwood City, California (The Bay Area), United States

Company

hirify.global develops the gStore platform, connecting physical retail stores, digital systems, hardware, IoT, AI applications, and enterprise SaaS.

What you will do

• Design and develop scalable systems across cloud, edge, and in-store environments.
• Define resilient and secure architectures for multi-tenant SaaS platforms.
• Build hardware-to-software interfaces and integrate RFID, IoT, and edge devices with cloud platforms.
• Develop GCP cloud-native applications and microservices using Kubernetes, containers, Kafka, Redis, BigQuery, and MongoDB.
• Build backend systems with Java, Python, and Node/NPM-based frameworks.
• Integrate AI/ML model outputs into production applications, data pipelines, analytics, and retail workflows.

Requirements

• 7+ years of software engineering experience with deep system-level exposure; the posting indicates 10–15 years of required experience.
• Bachelor’s degree in Computer Science, Electrical Engineering, or a related field, or equivalent practical engineering experience.
• Experience with cloud-native SaaS systems, preferably GCP, multi-tenant architectures, Kubernetes, container orchestration, and microservices.
• Strong expertise in Java with Spring Boot, Python frameworks, Node/NPM, Kafka, Redis, MongoDB, and BigQuery.
• Experience designing scalable distributed systems and understanding hardware-software interaction patterns.
• Ability to work from Redwood City, California.

Nice to have

• Experience with RFID systems and IoT integration.
• Background in retail technology or operational systems.
• Experience with AI/ML modeling and productionizing models.
• Experience building edge-to-cloud architectures.

Culture & Benefits

• Hands-on engineering role with strong ownership and pragmatic execution.
• Close collaboration across teams and participation in design reviews and technical strategy discussions.
• Fast-paced startup environment focused on technical excellence.
• Focus on scalable architecture, reliable hardware-cloud integration, and maintainable high-performance code.