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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI/ML Developer - **Company:** AI Powered LLC - **Location:** Pleasanton, CA, United States - **Experience:** Expert - **Salary:** $130,000.0 - $135,000.0 - **Contract:** Contract - **Skills:** A/B Testing, Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Automation of Tests, Big Data, BigQuery, Cloud Computing, Cluster Analysis, Computer Programming, Continuous Integration, Information Engineering, Cursor, DevOps, Data Flow Control, Github, Python (Programming Language), Machine Learning, Oracle (Applications), Recommender Systems, Tensorflow, Standard Sql, Systems Architecture, Jupyter Notebook, Feature Store, Google Cloud, Feature Engineering, Graph Neural Networks, GitHub Copilot, Pytorch, Large Language Models, Apache Spark, Model Validation, AI-powered Productivity Tools, Pandas, Containerization, Scikit Learn, Kubernetes, Real-time Inference, Information Technology, Optimization Algorithms, Data Analytics, Xgboost, Plotly, Machine Learning Operations, Restful APIs, Terraform, Looker Analytics, GPT, Software Version Control, Data Pipelines, Docker, Unsupervised Learning, Microservices - **Published:** October 23, 2026 - **Apply:** https://www.dice.com/job-detail/8b9d4b51-a74e-4c65-aa26-e64292f17187 ## About the Role Are you a data-driven engineer who sees patterns where others see complexity? Do you enjoy building intelligent systems that solve real-world business challenges? We are seeking an experienced AI/ML Software Engineer (P3) to help design, build, and scale next-generation AI solutions that drive smarter decision-making across the food supply chain., * Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience). * 5+ years of experience developing and deploying machine learning solutions in production environments. * Proven ability to translate complex business challenges into effective machine learning solutions. * Strong expertise in: + Supervised and unsupervised learning + Time-series forecasting + Classification + Clustering * Solid software engineering fundamentals, including: + Version control + Automated testing + Documentation + AI/ML system architecture * Experience working in cloud-native environments with containerization and CI/CD practices. * Strong communication skills with the ability to explain complex technical concepts to technical and non-technical audiences. * Experience supporting real-time inference, large-scale batch predictions, and model retraining workflows., * Experience with: + Optimization algorithms + Recommendation systems + Large Language Models (LLMs) + Graph Neural Networks (GNNs) * Experience applying AI solutions within supply chain, logistics, forecasting, or operations environments. Technical Skills Programming & Machine Learning * Python * SQL * TensorFlow * PyTorch * Scikit-learn * XGBoost Data Engineering * Oracle * BigQuery * Apache Spark * Apache Airflow * Pandas * dbt, You naturally look for opportunities to embed intelligence into solutions rather than treating AI as an afterthought. Bias for Action You thrive in fast-paced environments, embrace ambiguity, and adapt quickly to evolving technologies and business needs. Ownership Mentality You proactively identify opportunities, solve problems independently, and take accountability for outcomes. Trust Builder ## Description In this role, you will develop and deploy machine learning models, create scalable data pipelines, and collaborate cross-functionally to deliver AI-powered products from concept through production. This is an opportunity to work with modern AI technologies and apply them to high-impact business problems at scale. What You'll Do Build Intelligent Systems * Design, develop, and deploy scalable machine learning models and data pipelines. * Create solutions for supply chain optimization, demand forecasting, and anomaly detection. * Ensure models are interpretable, reliable, and production-ready. AI-Powered Product Development * Partner with Product Managers, Software Engineers, and Data Scientists to integrate machine learning solutions into customer-facing products. * Drive projects through the full lifecycle, from ideation to production deployment. Data Engineering & Analytics * Work with large-scale datasets sourced from transactional systems, IoT sensors, and third-party providers. * Build and maintain data pipelines using technologies such as BigQuery, Airflow, Spark, and dbt. * Perform data exploration, feature engineering, and transformation activities. Model Development & Optimization * Develop and train machine learning and deep learning models using Python, TensorFlow, PyTorch, XGBoost, and Scikit-learn. * Conduct model evaluation, experimentation, A/B testing, and performance benchmarking. * Continuously optimize models for accuracy, scalability, and efficiency. MLOps & Deployment * Deploy machine learning solutions using Docker, Kubernetes, and CI/CD pipelines. * Monitor model performance, drift, and reliability in production environments. * Build robust MLOps frameworks that support model versioning, reproducibility, and automated retraining. Innovation & Continuous Improvement * Stay current with emerging AI/ML technologies and industry trends. * Evaluate and implement new tools and approaches that create measurable business value., MLOps & DevOps * MLflow * Docker * Kubernetes * GitHub Actions * Terraform Cloud Platforms * Google Cloud Platform (Google Cloud Platform) + BigQuery + Vertex AI + Dataflow + Cloud Functions * Amazon Web Services (AWS) + SageMaker AI Productivity Tools * GitHub Copilot * ChatGPT * Cursor AI * Otter AI Analytics & Visualization * Looker * Plotly * Dash * Jupyter Notebooks Additional Technologies * REST APIs * Feature Stores * Microservices Architecture