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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Engineer - ACG / AEA - **Company:** Connected Logistics - **Location:** Springfield, VA, United States (Remote available) - **Experience:** Expert - **Salary:** $155,000.0 - $165,000.0 - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Automated Storage and Retrieval Systems, Automation of Tests, Microsoft Azure, Cloud Computing, Encodings, Continuous Integration, Python (Programming Language), Machine Learning, Performance Tuning, Tensorflow, Service Design, Service Development Studio, Software Engineering, Enterprise Software Applications, Feature Engineering, Pytorch, Flask (Web Framework), Large Language Models, Model Validation, Fastapi, Containerization, Scikit Learn, Information Technology, Low Latency, Machine Learning Operations, Restful APIs, Software Version Control, Data Pipelines, Devsecops, Serverless Computing, Docker, Microservices - **Published:** July 3, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/17475884?backUrl=%2Fcareer%2F17475884%2FAi-Ml-Engineer-Acg-Aea-Virginia-Springfield ## About the Role * Minimum 10 years of experience in AI/ML engineering, software development, or data science. * Master's degree required in Computer Science, Engineering, or related field. * Must have an Active Public Trust clearance or higher. * Strong experience with Python and ML frameworks (PyTorch, TensorFlow, scikit-learn). * Experience with embeddings, vector similarity search, and retrieval systems. * Experience building and deploying APIs or microservices for ML inference. * Hands-on experience with AWS and/or Azure environments. * Experience integrating into CI/CD pipelines and production systems. Must-Have Skill Sets (Technical + Methodologies) RAG Implementation (hands-on build experience) * Document ingestion + chunking strategies * Embedding generation and storage * Vector similarity search and retrieval optimization Machine Learning Model Development * Classification, clustering, and ranking models * Feature engineering and dataset preparation * Model tuning and evaluation ## Description * Develop ML models and supporting services for classification, clustering, similarity search, and prediction. * Implement RAG pipelines: document ingestion, embedding generation, vector indexing, and retrieval tuning. * Build APIs and microservices to expose model capabilities to enterprise systems. * Integrate ML components into existing DevSecOps pipelines (Azure DevOps, CI/CD workflows). * Implement duplicate detection, ticket routing, SLA prediction, and root-cause assist features. * Optimize model performance for latency, throughput, and accuracy. * Conduct model evaluation, error analysis, and iterative tuning. * Work with Data Engineer to align data pipelines with model input requirements. * Ensure outputs are explainable, auditable, and compliant with governance controls., * Prompt construction and chaining * Output validation and structured responses * Integration of LLMs into workflows (not just experimentation) API and Service Development * RESTful API design and implementation * Serving ML models in production (FastAPI, Flask, etc.) * Stateless service design CI/CD for ML Systems * Model deployment pipelines * Automated testing and validation before release * Version control for code + models Cloud Deployment * Running ML workloads in AWS or Azure * Containerization (Docker) * Basic orchestration patterns (serverless or container-based) Search and Similarity Systems * Embeddings + cosine similarity / ANN search * Duplicate detection patterns * Ranking and scoring logic Performance Optimization * Latency reduction for inference * Efficient batching / caching strategies * Memory and compute-tuning ## Related Videos - [Navigating the AI Revolution in Software Development](https://www.wearedevelopers.com/videos/1266-navigating-the-ai-revolution-in-software-development) - [Intro to FastAPI](https://www.wearedevelopers.com/videos/462-intro-to-fastapi) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [How AI Models Get Smarter](https://www.wearedevelopers.com/videos/1374-how-ai-models-get-smarter) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift)