Senior / Staff ML Engineer

BS or MS in Computer Science, Statistics, Mathematics, Physics, or a related quantitative field; PhD is a plus but not required
8+ years (Staff) / 5+ years (Senior) of experience in quantitative analysis, statistical modeling, and deploying ML solutions to production
Strong command of advanced statistical techniques, including regression, hypothesis testing, and distributions, with practical experience applying them to real-world problems
Deep understanding of machine learning algorithms, including decision trees, clustering, neural networks, and their trade-offs in production environments
Hands-on experience with LLMs and generative AI (e.g., prompt engineering, Agent frameworks, fine-tuning, RAG, or LLMOps)
Proficient in Python and SQL, with experience in ML libraries such as PyTorch, TensorFlow, and XGBoost
Familiar with data modeling and pipeline development using dbt, with the ability to design clean, scalable transformations that support downstream ML applications
Working knowledge of modern data/ML infrastructure (e.g., Airflow, MLFlow, feature stores, vector databases, CI/CD for ML)
Strong communication and documentation skills with the ability to collaborate cross-functionally

Build/integrate new machine learning models into production using the necessary tools to monitor/administer them
Collaborate with cross-functional teams to set and align on machine learning platform strategies to meet company objectives
Deliver best-in-class technical approach and problem analysis documents
Impact key company objectives by working closely with Product to refine our roadmap
Build/maintain reports, dashboards, and metrics to monitor the performance of our products
Mentor junior team members helping them to grow their skills and expertise
Drive key architectural decisions and contribute to our ML platform architecture and strategy
Act as a data evangelist to create a data-driven culture across the company and provide mentorship/feedback to analysts and other data-minded stakeholders