AI/ML Engineer
Summary
Builds and deploys ML/data applications and APIs, engineers large-scale data pipelines (Spark/PySpark, Elasticsearch, ETL/ELT), and operates ML models and inference services across cloud, containerized, and GPU/CPU environments in support of geospatial intelligence solutions for Defense, Intelligence, and Federal clients. Requires an active TS/SCI clearance and 10+ years of software engineering ex
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.
Skills
As published by lever · 2 questions
Basics
Resume/CV, Full name, Email, Phone, Current location, Current company, LinkedIn URL
Pick from a list (2)
- Are you a U.S. citizen? optional
- What is your current level of government security clearance? optional