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.