AI/ML Engineer - ACG / AEA

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.
• CID/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