AI/ML Engineer

IntelliTrans • Dunwoody, GA

23h • Hybrid

About The Position

The Applied AI Engineer is a key member of the AI and Data Science Team, responsible for designing, developing, and deploying production AI/ML systems that power IntelliTrans’ intelligent freight management platform. This role blends applied AI engineering with data science fundamentals, including building and evaluating agentic AI systems, developing LLM-powered features, designing ML pipelines, and creating intelligent automation workflows. The ideal candidate is comfortable operating across the full spectrum from exploratory data analysis to production AI system deployment and is energized by applying AI to real-world logistics challenges.

Requirements

• Bachelor’s degree in Computer Science, Data Science, Machine Learning, Applied Mathematics, or related discipline required.
• Minimum 2–4 years of professional experience in AI engineering, ML engineering, or applied data science (combination of internships and professional experience considered).
• Demonstrated experience building and deploying AI systems, ML models, or LLM-powered applications in a production environment.
• Experience with modern data platforms, preferably Databricks (Delta Lake, MLflow, Unity Catalog) or equivalent (Snowflake, AWS SageMaker).
• Strong proficiency in Python, including experience with FastAPI, pandas, scikit-learn, and async programming patterns.
• Solid working knowledge of SQL and experience with experience with relational databases (PostgreSQL preferred, Oracle experience a plus).
• Experience with cloud platforms, primarily AWS (ECS, S3, SQS, Lambda, CloudWatch, Bedrock).
• Familiarity with ML experiment tracking, model versioning, and MLOps workflows (MLflow preferred).
• Proficiency with approaches to statistical analysis, mathematical modeling, and data visualization.
• Knowledge of Infrastructure as Code (Terraform), containerization (Docker), and CI/CD pipelines (GitLab).
• Experience with observability tools (OpenTelemetry, CloudWatch, structlog) for production ML systems.
• Strong analytical and problem-solving abilities with the capacity to operate across ambiguity.
• Excellent communication skills, including the ability to present complex technical results to executive and non-technical audiences.
• Self-directed learner comfortable rapidly adopting emerging AI/ML technologies and frameworks.
• Collaborative mindset suited to cross-functional, agile team environments.
• Intellectual curiosity about logistics, supply chain, and freight management domain problems.

Nice To Haves

• Master’s degree in a quantitative field (Data Science, AI/ML, Engineering, Mathematics, or Statistics) preferred.
• Experience in supply chain, logistics, freight management, or transportation technology is strongly preferred.
• Hands-on experience with agentic AI concepts, LLM integration patterns, or RAG architecture is preferred.
• Experience creating and deploying AI Agents to production using Agentic Libraries and platforms.
• Familiarity with document intelligence, and multimodal AI capabilities.

Responsibilities

• Design, build, and evaluate agentic AI systems using Agentic AI platforms and related frameworks for freight management use cases (e.g., shipment exception handling, real time visibility, ETA intelligence).
• Develop and optimize LLM-powered features, including prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and tool-calling agents integrated into workflows.
• Build and maintain ML model evaluation frameworks with structured metrics, AI-assisted judges, and human feedback loops modern frameworks and DB Catalog tools.
• Contribute to developing browser automation + AI hybrid systems, including data extraction pipelines using Playwright and Claude.
• Analyze complex, large-scale freight and logistics datasets to generate actionable business insights for internal stakeholders and customers.
• Develop and maintain predictive models for supply chain KPIs, including ETA prediction, freight audit anomaly detection, and shipment pattern analysis.
• Support IntelliTrans’ data streaming strategy by designing data pipelines and feature engineering workflows that bridge the System of Record and System of Intelligence layers.
• Build and iterate on dashboards and analytical tools using SQL, Analytics, and supporting visualization platforms.
• Develop production-grade Python services (FastAPI, async patterns) that integrate ML models and AI agents into the IntelliTrans platform.
• Collaborate with the architecture team on AWS cloud infrastructure (ECS Fargate, SQS, S3, CloudWatch, Terraform) for model deployment and agent runtime scaling.
• Contribute to CI/CD pipelines, observability instrumentation (OpenTelemetry, structlog), and MLOps best practices for model lifecycle management.
• Partner with Product Management to translate the AI agent roadmap into technical specifications and delivery plans aligned with IntelliTrans’ 3–5 year data and AI strategy.
• Use modern Code Assistance tools such as Claude Code to write software.
• Effectively handle multiple projects simultaneously in a deadline-driven environment.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level