iTradeNetworkposted 3 days ago
Charlotte, NC
Computer and Electronic Product Manufacturing
JOB SUMMARY
We are seeking an AI/ML Engineer who's ready to take the wheel in shaping our next-generation AI products. You'll help architect and deploy intelligent systems that directly drive smarter decision-making across the food supply chain.
This isn't just another ML job-it's an opportunity to apply cutting-edge machine learning techniques to real-world, high-impact problems at scale.
Key Responsibilities:
* Build Intelligent Systems: Design, develop, and deploy ML models and pipelines that are scalable, interpretable, and optimized for real-world use cases in supply chain optimization, forecasting, and data anomaly detection.
* AI-First Product Development: Collaborate with product managers, engineers, and data scientists to integrate models into customer-facing applications and services. Take projects from concept to production.
* Data Engineering & Exploration: Work with massive, diverse datasets from transactional, sensor, and third-party sources. Create data pipelines and transformations using tools like BigQuery, Airflow, and Spark.
* Model Experimentation & Tuning: Train and optimize classical and deep learning models using Python, TensorFlow, PyTorch, XGBoost, and Scikit-learn. Apply rigorous testing, A/B experimentation, and performance benchmarking.
* Deploy at Scale: Operationalize ML models using Docker, Kubernetes, and CI/CD pipelines on GCP. Monitor drift, accuracy, and performance in production.
* Own the Pipeline: Build and maintain robust MLOps workflows that enable reproducibility, model versioning, and automated retraining using MLflow or similar frameworks.
* Drive Innovation: Stay ahead of the curve by evaluating emerging AI/ML technologies and integrating them into our toolchain where they create real value.
Tech Stack & Tools
* Languages & Libraries: Python, SQL, TensorFlow, PyTorch, Scikit-learn, XGBoost
* Data Engineering: Oracle, BigQuery, Spark, Airflow, Pandas, dbt
* MLOps & Deployment: MLflow, Docker, Kubernetes, GitHub Actions, Terraform
* Cloud: GCP (BigQuery, Vertex AI, Dataflow, Cloud Functions), AWS (SageMaker)
* AI Tools: GitHub Copilot, ChatGPT, Cursor AI, Otter AI
* Visualization & Analysis: Looker, Plotly, Dash, Jupyter
* Other: RESTful APIs, Feature Stores, Microservices Architecture
What you'll need:
* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or equivalent hands-on experience
* 5+ years of experience building and deploying machine learning solutions in production
* Proven ability to translate business problems into machine learning problems-and solve them
* Expertise in supervised and unsupervised learning, time-series forecasting, classification, and clustering
* Strong software engineering fundamentals: version control, testing, documentation
* Experience working in cloud-native environments with CI/CD and containerization tools
* Ability to explain complex ML concepts to technical and non-technical audiences
* Experience with real-time inference, large-scale batch predictions, and model retraining workflows
Nice-to-Have Qualifications:
* Bonus: Knowledge of optimization, recommendation systems, LLMs, or graph neural networks
If you are a highly motivated and results-driven individual, with a passion for driving growth in a fast-paced, entrepreneurial environment, we encourage you to apply for this exciting opportunity. We offer a competitive salary, comprehensive benefits package, and a dynamic work culture that values collaboration, innovation, and personal development.
We are seeking an AI/ML Engineer who's ready to take the wheel in shaping our next-generation AI products. You'll help architect and deploy intelligent systems that directly drive smarter decision-making across the food supply chain.
This isn't just another ML job-it's an opportunity to apply cutting-edge machine learning techniques to real-world, high-impact problems at scale.
Key Responsibilities:
* Build Intelligent Systems: Design, develop, and deploy ML models and pipelines that are scalable, interpretable, and optimized for real-world use cases in supply chain optimization, forecasting, and data anomaly detection.
* AI-First Product Development: Collaborate with product managers, engineers, and data scientists to integrate models into customer-facing applications and services. Take projects from concept to production.
* Data Engineering & Exploration: Work with massive, diverse datasets from transactional, sensor, and third-party sources. Create data pipelines and transformations using tools like BigQuery, Airflow, and Spark.
* Model Experimentation & Tuning: Train and optimize classical and deep learning models using Python, TensorFlow, PyTorch, XGBoost, and Scikit-learn. Apply rigorous testing, A/B experimentation, and performance benchmarking.
* Deploy at Scale: Operationalize ML models using Docker, Kubernetes, and CI/CD pipelines on GCP. Monitor drift, accuracy, and performance in production.
* Own the Pipeline: Build and maintain robust MLOps workflows that enable reproducibility, model versioning, and automated retraining using MLflow or similar frameworks.
* Drive Innovation: Stay ahead of the curve by evaluating emerging AI/ML technologies and integrating them into our toolchain where they create real value.
Tech Stack & Tools
* Languages & Libraries: Python, SQL, TensorFlow, PyTorch, Scikit-learn, XGBoost
* Data Engineering: Oracle, BigQuery, Spark, Airflow, Pandas, dbt
* MLOps & Deployment: MLflow, Docker, Kubernetes, GitHub Actions, Terraform
* Cloud: GCP (BigQuery, Vertex AI, Dataflow, Cloud Functions), AWS (SageMaker)
* AI Tools: GitHub Copilot, ChatGPT, Cursor AI, Otter AI
* Visualization & Analysis: Looker, Plotly, Dash, Jupyter
* Other: RESTful APIs, Feature Stores, Microservices Architecture
What you'll need:
* Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or equivalent hands-on experience
* 5+ years of experience building and deploying machine learning solutions in production
* Proven ability to translate business problems into machine learning problems-and solve them
* Expertise in supervised and unsupervised learning, time-series forecasting, classification, and clustering
* Strong software engineering fundamentals: version control, testing, documentation
* Experience working in cloud-native environments with CI/CD and containerization tools
* Ability to explain complex ML concepts to technical and non-technical audiences
* Experience with real-time inference, large-scale batch predictions, and model retraining workflows
Nice-to-Have Qualifications:
* Bonus: Knowledge of optimization, recommendation systems, LLMs, or graph neural networks
If you are a highly motivated and results-driven individual, with a passion for driving growth in a fast-paced, entrepreneurial environment, we encourage you to apply for this exciting opportunity. We offer a competitive salary, comprehensive benefits package, and a dynamic work culture that values collaboration, innovation, and personal development.
