Top Remote Senior Level Machine Learning Engineer Jobs in CO

Lead ML feature strategy and engineering for fraud detection, owning end-to-end pipelines, validating features at scale, and translating analytics into production ML systems. Drive tooling and architecture decisions, mentor junior team members, partner cross-functionally with product and risk teams, and apply practitioner-level ML knowledge to detect and prevent account takeover and scam activity.

Lead design and delivery of low-latency market-making and automated trading strategies. Translate quantitative research into production systems, build backtesting and real-time decision engines, ensure scalability and observability, manage risk-aware optimization, and influence cross-functional teams on strategy and technical direction.

Lead machine learning initiatives to enhance underwriting model accuracy. Design and implement advanced training strategies and optimize workflows. Mentor engineers and influence modeling strategy.

Lead development and deployment of predictive models, analytics, and dashboards to support Sales, Marketing, Customer Success, and GTM operations. Mentor data scientists, partner with business leaders to prioritize analytics, ensure data governance and quality, and present insights to executives. Work with Snowflake/data lakes, build scalable ML solutions, and drive analytics adoption across the enterprise.

Lead the development of fraud prediction models using machine learning, collaborating across teams to build, scale, and monitor models in production.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

Develop scalable machine learning services for data enrichment, managing the ML lifecycle from model training to deployment, and ensuring performance and reliability standards.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

Lead design, development, and deployment of enterprise AI agents and multi-agent systems. Architect scalable, secure AI/data systems, integrate vector DBs, embeddings, RAG, and cloud MLOps, drive automation/APIs, mentor engineers, set KPIs, and ensure observability, ethical AI, and production readiness.