Forward Deployed Machine Learning Engineer

This is a fully remote position, open to applicants in North America.

📋 Description

• Engage in the development, deployment, and enhancement of machine learning models and workflow features that cater to genuine customer requirements.

• Utilize machine learning techniques to boost accuracy and enhance overall system performance, ensuring that solutions are robust, dependable, and ready for production use.

• Refine, implement, and verify machine learning models and workflows that facilitate submission intake, underwriting decision processes, and automation tasks.

• Deploy and customize autonomous agent behaviors within customer-specific workflows, converting core AI capabilities into actionable solutions.

• Create and sustain evaluation pipelines, monitoring systems, and performance metrics to guarantee reliability amidst changing production conditions.

• Oversee production systems through logs, metrics, and user feedback to identify issues, troubleshoot failures, and facilitate resolutions.

• Assume full ownership of issues—executing fixes or collaborating with engineering and infrastructure teams as necessary.

• Collaborate closely with Data Science and Engineering teams to iterate swiftly and deliver impactful solutions.

⛳️ Requirements

• Bachelor’s or master’s degree in Mathematics, Operations Research, Data Science, Artificial Intelligence, or a related discipline, with a solid foundation in machine learning, deep learning, and natural language processing.

• Experience in a dynamic, cross-functional environment.

• Over 2 years of experience as a Machine Learning Engineer, Applied Scientist, or in a comparable role delivering machine learning solutions in production.

• Experience collaborating directly with customers or stakeholders to convert business needs into technical solutions.

• Practical experience in adapting, extending, and deploying ML/LLM systems (including agentic workflows and prompt engineering) in real-world scenarios.

• Strong background in experimentation, evaluation, and monitoring pipelines, including the analysis of production logs and system debugging.

• Experience in deploying and iterating on ML systems in cloud environments in partnership with engineering teams.

• Demonstrated history of ownership—resolving issues effectively in production systems.

🏝️ Benefits

• The total compensation package includes stock options, benefits, and additional perks.