HiringCafe
Posted 1mo ago

AI Engineer

@ InterImage
View All Jobs
Annapolis Junction, Maryland, United States
OnsiteFull Time
Responsibilities:Designing AI, Developing models, Deploying systems
Requirements Summary:Strong Python, backend languages (Java/Go/C++/Scala), SQL; ML frameworks (TensorFlow, PyTorch, Scikit-learn, Hugging Face); AWS with MLOps; REST/gRPC; Docker/Kubernetes; CI/CD; big data (Spark/Hadoop); data modeling and analytics.
Technical Tools Mentioned:Python, Java, Go, C++, Scala, SQL, TensorFlow, PyTorch, Scikit-learn, Hugging Face, Docker, Kubernetes, Jenkins, GitLab CI, GitHub Actions, Terraform, CloudFormation, AWS, Spark, Hadoop, Flink, Kafka, PostgreSQL, MySQL, MongoDB, Elasticsearch, DynamoDB
Save
Mark Applied
Hide Job
Report & Hide
Job Description

Overview

We have an immediate need for an Artificial Intelligence (AI) Engineer to support TO-005, Report Authoring and Dissemination (RAD). This role will work closely with system and software engineers to design, prototype, and integrate AI-driven capabilities into the existing RAD architecture—while also contributing to the design of next-generation architecture built for scalability and large data processing.

This is a transformative opportunity to build systems from the ground up that augment human intelligence, streamline workflows, and enable data-driven decision-making across enterprise environments handling high-volume, complex datasets.

Key Responsibilities

AI Solution Design & Development

  • Lead end-to-end design and development of AI/ML solutions—from concept, prototyping, and architecture design to production deployment
  • Write production-grade code and contribute to scalable, maintainable software systems
  • Design modular, extensible architectures that support AI integration within enterprise platforms

Software Architecture & Engineering

  • Contribute to or lead the design of enterprise-grade software architecture from scratch, including microservices and distributed systems
  • Build backend services and APIs to support AI-driven applications and data pipelines
  • Ensure systems are designed for scalability, fault tolerance, and high availability
  • Implement best practices in software engineering, version control, CI/CD, and testing frameworks

Data Engineering & Large-Scale Processing

  • Design and implement data pipelines to ingest, process, and analyze large structured and unstructured datasets
  • Perform Exploratory Data Analysis (EDA) to inform model design and data strategy
  • Optimize data storage and retrieval for performance and scalability

Model Development & Deployment

  • Develop, train, evaluate, and fine-tune machine learning and deep learning models
  • Implement robust validation, testing, and monitoring to ensure model accuracy, fairness, and reliability
  • Deploy models into production environments using MLOps best practices

Collaboration & Communication

  • Serve as a technical liaison across engineering, data, and mission stakeholders
  • Clearly communicate AI approaches, tradeoffs, and system design decisions to both technical and non-technical audiences

Continuous Innovation

  • Stay current with emerging AI/ML technologies, frameworks, and enterprise data solutions
  • Identify opportunities to enhance system performance, automation, and intelligence capabilities