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# AI/ML Software Engineer

- **Company:** Macpower Digital Assets Edge LLC
- **Location:** Annapolis, MD, United States (Remote available)
- **Experience:** Experienced
- **Salary:** $120,000.0 - $149,000.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Apache HTTP Server, Relational Databases, Web Development, Middleware, Graph Database, Python (Programming Language), PostgreSQL, Machine Learning, Language Modeling, Neo4j, Performance Tuning, Service-Oriented Architecture, Software Engineering, Data Processing, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, HybridCloud, Backend, Agentic-AI, Git, Build Management, Containerization, Integration Tests, Information Technology, Api Design, Software Version Control, Data Pipelines, Docker
- **Published:** October 29, 2026
- **Apply:** https://www.thejobnetwork.com/job/10ae4987-35b6-4d29-9568-fe7c6655f344/aiml-software-engineer

## About the Role

* Bachelor of Science in Computer Science, Engineering, Data Science, Mathematics, or a related field.
 * At least 3 years of experience in data science, machine learning, or applied AI development.
 * At least 3 years of experience in software engineering, architecture, or web development.
 * Proven proficiency in Python for developing production-grade backend services, APIs, and middleware.

Preferred Experience:

 * Collaborating with Large Language Models (LLMs) via API-based integration and local deployment.
 * Implementing RAG systems using embedding models, vector similarity, re-ranking, and graph retrieval.
 * Working with SQL/relational databases (e.g., PostgreSQL) and graph databases (e.g., Neo4j, Apache AGE).
 * Fine-tuning small language models or embedding models.
 * Designing multi-agent or task-oriented AI systems.
 * Utilizing version control (Git) and containerization (Docker) within service-oriented architectures.

## Description

* Design and implement software systems that integrate AI/ML techniques to automate specific tasks with high accuracy.
 * Develop agent architectures, workflows, and system designs in collaboration with cross-functional teams.
 * Build and deploy containerized applications within hybrid cloud environments.
 * Determine optimal approaches for technical challenges, including the selection between LLM-based and non-LLM techniques.
 * Optimize system performance for environments with limited computational resources and minimal GPU availability.
 * Create robust testing and evaluation pipelines, including the generation of synthetic data for benchmarking.
 * Develop unit and integration tests for AI-enabled workflows and backend data pipelines.
 * Document all system designs, technical decisions, and workflows to ensure production-grade quality.
 * Contribute to high-level decision-making regarding data processing and retrieval strategies.