Staff AI Distributed Research Engineer (AI, Distributed Systems)

TL;DR

Staff AI Distributed Research Engineer (AI, Distributed Systems): Architecting and optimizing AI-based imaging and audio algorithms for distributed execution across cloud and edge devices with an accent on real-time streaming platforms and unified data models. Focus on translating cutting-edge ideas into production-ready systems and championing data governance practices.

Location: Hybrid, Atlanta, Georgia, United States. Salary range for this position is specific to the Atlanta Area but can vary for other US locations.

Salary: $170,000 – $187,000 (yearly)

Company

hirify.global is a leader in entertainment innovation, delivering insights and technological solutions in areas like AI/ML, distributed systems, and audio/video processing.

What you will do

• Architect and optimize AI-based imaging and audio algorithms for distributed execution.
• Design and implement scalable, low-latency cloud backends and real-time streaming platforms.
• Collaborate with researchers to translate cutting-edge ideas into production-ready systems.
• Build unified data models and metadata services for AI/ML training and inference.
• Develop novel tools for data collection, instrumentation, and context inference using AI techniques.
• Champion data governance and management practices.

Requirements

• Master’s in Computer Science or a related field (PhD preferred).
• 5+ years of experience designing and building distributed data systems.
• Deep experience in distributed systems, real-time streaming, and cloud-native architectures.
• Strong proficiency in Python and one or more systems-level languages (e.g., C++, Golang, Rust).
• Expertise in data structures, distributed algorithms, and heterogeneous data analytics.
• Proven track record of delivering impactful, scalable solutions in cloud and edge environments.

Nice to have

• Familiarity with real-time messaging frameworks (Kafka, Flink, Spark Streaming).
• Knowledge of AI/ML models, cloud optimization, and DevOps practices.
• Experience with deep learning frameworks (TensorFlow, PyTorch) and Databricks/Spark.
• Understanding of audio/video formats, streaming protocols, and media processing pipelines.

Culture & Benefits

• Collegial culture with challenging projects and excellent compensation.
• Flex Work approach to support where, when, and how you do your best work.
• Committed to making employment decisions without regard to various classifications.