Top Remote Senior Level Machine Learning Engineer Jobs in CO

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.

As a Staff Machine Learning Engineer, you will design AI products on Edge devices, optimize ML model performance, and work with large-scale datasets, collaborating across teams to deliver impactful solutions.

The Senior Machine Learning Engineer will design, implement, and optimize machine learning models, drive AI initiatives, and collaborate cross-functionally to enhance SailPoint's AI capabilities.

Lead design, development, and deployment of production-grade, large-scale ML systems. Influence ML strategy, integrate models with platform and data infrastructure, mentor engineers, communicate results to stakeholders, and mature ML infrastructure and abstractions across teams.

The Staff Machine Learning Engineer will lead ML initiatives, develop ML systems, collaborate with cross-functional teams, and mentor junior engineers to optimize healthcare intake workflows using advanced machine learning techniques.

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

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