AI/ML Engineer - ACG / AEA at Connected Logistics

, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

01 Oct, 26

Salary

165000.0

Posted On

03 Jul, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

RAG Implementation, Machine Learning, Python, PyTorch, TensorFlow, Scikit-learn, Vector Similarity Search, API Development, AWS, Azure, CI/CD, Docker, LLM Application Development, FastAPI, Flask, Prompt Engineering

Industry

Defense and Space Manufacturing

Description

Description Remote Contingent Contract Award 6 month opportunity Springfield, VA Connected Logistics is seeking an AI/ML Engineer to build and integrate machine learning components into enterprise workflows. The focus is on implementing models, RAG pipelines, and supporting services that enable automation, classification, retrieval, and intelligent decision support. Ideally, the engineer should have prior successes building and deploying RAG + ML services in production. This opportunity is expected to last for six (6) months with travel to Washington, DC. Key Responsibilities: 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. Requirements 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 LLM Application Development 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 Total Rewards Statement: We believe in fairness and clarity throughout our hiring process. The anticipated salary range for this position is $155,000.00 to $165,000.00 good faith range based on factors such as your experience, geographic location, and any applicable contractual requirements, and may vary slightly. Beyond salary, we provide a robust benefits package and encourage ongoing professional development, because your growth and well-being matter to us. We’re excited to support you in building a rewarding career with us! Connected Logistics respects the need for confidentiality for all applicants. Connected Logistics offers an excellent benefits package that includes health, dental, vision, life, and disability insurance, a great 401(k) package, and generous Paid Time Off. EOE/Disability/Veterans

Responsibilities

Develop and integrate ML models and RAG pipelines into enterprise workflows for automation and intelligent decision support. Build APIs and microservices while integrating components into DevSecOps pipelines.