Staff Engineer - Recommendations

Overview

This position is with a partner company located in Ireland, specializing in building the foundational data and machine learning systems that enable personalized discovery and social interactions at scale. The Staff Engineer will focus on developing recommendation systems that enhance connections between users and relevant content, communities, groups, and events.

Responsibilities

• Design, implement, maintain, and optimize scalable data pipelines, backend services, and APIs that support recommendations, content discovery, groups, events, and other data-driven features.
• Create data models and schemas tailored for analytical queries and real-time personalization and recommendation tasks.
• Collaborate with data scientists, product managers, and engineering teams to ensure accurate capture, processing, and availability of important user and platform data for product functionality.
• Build and oversee large-scale data processing workflows utilizing frameworks such as Spark and Kafka.
• Advance recommendation systems from basic heuristic-based approaches toward advanced, data-centric personalization models.
• Contribute to backend architectural design and implementation, including RESTful and WebSocket APIs, caching layers, messaging queues, and cloud orchestration.
• Transform high-volume platform data into dependable datasets and signals for machine learning and personalization use cases.
• Improve data storage solutions, processing efficiency, and database performance for both analytical and real-time high-throughput applications.
• Work in a full-stack engineering context to deliver scalable and reliable features, spanning data infrastructure to user-facing experiences.
• Participate in shaping technical strategy and evolving engineering and product capabilities aligned with growing needs in recommendation and personalization.
• Engage in production system monitoring and incident management, occasionally providing critical support during outages.
• Champion best engineering practices focusing on scalability, reliability, maintainability, observability, and data integrity.

Requirements

• At least 3 years of professional experience as a software engineer, concentrating on data engineering, backend systems, or scalable SaaS/online platforms.
• Demonstrated expertise in designing, developing, and tuning production-level ETL/ELT pipelines.
• Proficient in SQL with strong capabilities in database optimization for both analytical and high-throughput real-time queries.
• Hands-on experience with big data technologies such as Spark, Kafka, Hadoop, or Beam.
• Experience managing cloud platforms at scale, particularly AWS or Google Cloud.
• Programming proficiency in Python, JavaScript/Node.js, MongoDB, and Redis, with an aptitude for working across multiple languages and platforms.
• Knowledge of Elasticsearch, data warehousing, and machine learning systems.
• Deep understanding of scalable backend architectures, distributed data processing, APIs, caching systems, queue infrastructures, and cloud orchestration.
• Ability to collaborate effectively across cross-functional teams, including data scientists and product managers.
• Excellent communication skills and a collaborative mindset adapted to a distributed engineering environment.
• Preferred experience includes working with content discovery platforms, recommendation engines, personalization technologies, social graphs, online communities, or user-generated content.
• Background in building consumer products, e-commerce platforms, marketplaces, or social applications is highly beneficial.
• Interest or familiarity with virtual reality, online communities, or creator-driven ecosystems is considered a plus.

Benefits

• Work completely remotely with flexible scheduling and core collaboration hours.
• Comprehensive health benefits.
• 401(k) plan available for qualified U.S. employees.
• Equity stock options.
• Generous paid holidays and unlimited, flexible vacation policy.
• Paid parental leave.
• Chance to influence and work on large-scale recommendation, data, and personalization systems.
• Engage in a collaborative, distributed team environment where engineers can contribute ideas and shape technical directions.

Additional Information

The application process utilizes AI to streamline candidate evaluation fairly and efficiently, focusing on alignment with core requirements. Final hiring decisions and next steps are managed directly by the hiring company's internal team. Privacy is respected and protected in accordance with relevant laws, with transparency about data processing activities.