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

📋 Description

• Develop top-notch machine learning models aimed at identifying subrogation opportunities by leveraging cutting-edge ML innovations and best software engineering practices.

• Engage with and collaborate alongside business stakeholders, including customers, sales teams, and product managers, to spearhead the creation of new models and features.

• Work in conjunction with data engineering and software engineering teams to guarantee seamless data integration across teams and APIs associated with outbound subrogation.

• Provide mentorship to junior ML engineers within the outbound subrogation team to cultivate a high-performing unit.

⛳️ Requirements

• Profound knowledge of the machine learning lifecycle: development, assessment, deployment, monitoring, and iterative improvement.

• Exceptional communication abilities, with a knack for articulating intricate technical concepts to non-technical stakeholders.

• Practical experience in experimental design and model assessment.

• Proficiency in ML system architecture, model deployment, and operational ML frameworks.

• Experience in engineering production-quality GenAI features with comprehensive validation, sanity checks, and structured outputs to minimize hallucinations and business risks.

• Skilled in the AWS ML ecosystem, including SageMaker, Lambda, Step Functions, and IAM.

• Solid understanding of software engineering principles and best practices, such as CI/CD, Test-Driven Development, and Infrastructure as Code.

• Capability to translate business goals into technical roadmaps and actionable deliverables.

• Ability to harmonize technical excellence with business priorities and timelines.

• Strong skills in stakeholder management and cross-functional collaboration.

• English proficiency: Upper-Intermediate.

• Experience in subrogation, claims processing, insurance, or financial technology is a plus.