AI/ML Engineer

Job description

Reinventing Geospatial (RGi) is a leading expert in geospatial solutions for Defense, Intelligence, and Federal clients. We enhance situational awareness for soldiers and analysts by integrating software development with geospatial intelligence. Our projects range from data collection to advanced deep learning, leveraging tools like Python, Java, and ArcGIS. We don't just fill roles we build teams of high performers and leaders who make an immediate impact. At our core, we're driven by innovation and powered by people who work at the intersection of passion and performance. Here, you'll collaborate with bold thinkers, leverage cutting edge technology, and tackle meaningful challenges from day one. Our culture is defined and anchored by three pillars: **Energy:** We bring passion, purpose, and urgency to our work. **Edge:** We take initiative, embrace growth, and step outside our comfort zone. **Execution:**We get things done smartly, decisively, and with real results. If you're the kind of person who leads with initiative, thrives in a fast-paced environment, and is eager to create real impact, we want you on our team. ### As a AI/ML Engineer you will... - Build and deploy data/ML applications and APIs that turn analytics and machine-learning capabilities into reliable production services. - Engineer and manage large-scale data pipelines and platforms, including data modeling, ETL/ELT, transformation, data quality, and distributed technologies like Spark/PySpark and Elasticsearch. - Translate mission/customer needs into scalable technical solutions, including deploying and operating ML models and inference services across cloud, containerized, and GPU/CPU environments. - Collaborate with mission, engineering, and data teams to design practical solutions that connect customer needs, data, analytics, software, and machine learning. ### AI/ML Engineer Qualifications: - Must have a current/active TS/SCI and be willing and able to obtain a CI polygraph - Bachelors degree in a relevant field. Equivalent years of experience may be substituted in lieu of a degree. - At least 10+ years of experience as in software engineering, with 2+ years AI/ML focus. - Experience developing and deploying analytics, machine learning, or data-intensive applications and services. - Experience building APIs or production services using technologies such as FastAPI, Django, Java, or equivalent frameworks. - Experience with data modeling, ETL/ELT, data quality, transformation logic, and analytical or search-oriented data stores. - Ability to translate ambiguous mission or customer problems into practical data, analytics, and software solutions. - Experience with distributed data engineering using Apache Spark/PySpark, HDFS, Delta Lake, Elasticsearch, or similar technologies across large-scale datasets. - Experience deploying and operating machine learning models and inference services at scale across GPU/CPU clusters or containerized environments. - Strong data engineering background is a plus. - Previous experience with Apache NiFi.