RIVA Solutions, Inc. - Artificial Intelligence and Machine Learning Engineer

• Bachelor's degree in Computer Science, Data Science, Engineering, or a related field. • 5+ years of applied ML, data science, or AI engineering experience, including 2+ years building applications on large language models in production or near-production settings. • Strong Python skills, including data work with pandas or PySpark. • Solid ML fundamentals: classification, train and test splits, overfitting, data leakage, and model selection. • Hands-on evaluation skill: precision, recall, F1, confusion matrices, class imbalance, and comparison to labeled ground truth. • Production experience building with LLM APIs, including structured output, tool calling, and prompt design. • Experience building or debugging an agent harness, and the judgment to explain when a structured pipeline is the better choice. • Experience validating LLM output with schemas (for example, Pydantic or JSON Schema), retries, and exception handling. • Daily use of AI coding assistants such as Claude Code, Codex, Cursor, or GitHub Copilot. • Hands-on experience building and running ML or LLM workloads on Databricks or a major cloud platform (AWS, Azure, or GCP). Examples: data pipelines in PySpark or notebooks, calling hosted models through Databricks Model Serving, Amazon Bedrock, Amazon SageMaker, Azure OpenAI, Azure Machine Learning, or Vertex AI, and tracking experiments in MLflow. • AWS Certified Machine Learning Engineer - Associate, or an equivalent cloud ML certification. An active AWS Certified Machine Learning - Specialty also counts. • Eligibility to obtain a USPTO Public Trust and authorization to work in the U.S. • Databricks experience, including Jobs, Delta Lake, MLflow, and Unity Catalog. PyTorch experience, including fine-tuning small language models or training LoRA adapters. • AWS experience, including Amazon Bedrock. • Information extraction from scanned or long documents, including OCR and layout analysis. • Retrieval augmented generation and vector databases. • MLOps experience: pipeline orchestration, evaluation sets run in CI, and monitoring of output quality over time. • Experience working through an enterprise AI gateway with cost tracking and request filtering. • Databricks Certified Machine Learning Professional, Databricks Certified Machine Learning Associate, Databricks Certified Generative AI Engineer Associate, AWS Certified Machine Learning Engineer - Associate, or an equivalent cloud certification. • Experience with USPTO, PTAB, or patent and legal data. • Prior delivery on federal government contracts, including FISMA Moderate systems. • The salary or salary range for this role reflects an estimated range informed by multiple compensation factors. Final offers may vary based on considerations such as relevant experience, education and training, critical skillsets, and overall business needs. • $180,000 - $190,000 USD • EQUAL EMPLOYMENT OPPORTUNITY & ACCOMMODATION • We believe great teams are built from different backgrounds, perspectives, and lived experiences, and we mean that beyond the buzzwords.