Machine Learning Engineer

About The Company

Remotely is a pioneering fintech leader in Germany, focusing on innovative solutions to transform the credit marketplace. As Continental Europe's largest credit platform, it bridges private and institutional investors to pre-approved loans, promoting transparency and efficiency. The company blends start-up agility with the reliability of an established organization and promotes a diverse, inclusive culture across its offices in Düsseldorf, Budapest, and Dublin. Creativity, responsibility, and sustainability are core values driving its professional development opportunities.

Role Overview

The Machine Learning Engineer will play a key role within the Pricing team, responsible for transitioning ML models into stable, scalable production services that impact pricing strategies at scale. This position entails end-to-end ownership of ML models, from development through deployment and ongoing monitoring. Collaborating closely with Data Science, Data Infrastructure, and business units, the engineer will develop robust technical solutions to power the Dynamic Pricing platform. The role offers remote work options within Germany or hybrid arrangements in Düsseldorf or Berlin.

Key Responsibilities

• Manage the full lifecycle of ML models, ensuring reliable deployment and continuous monitoring in production systems.
• Drive operationalization of ML models to maintain stability, scalability, and maintainability, addressing common production challenges.
• Implement and support training pipelines within Snowflake-based data environments to integrate ML workflows effectively.
• Design and enhance applications supporting the Dynamic Pricing System to embed ML-driven pricing logic.
• Maintain a comprehensive understanding of intricate system landscapes to seamlessly integrate ML components within existing architecture and data flows.
• Liaise with cross-functional teams to convert business and analytics needs into effective technical implementations that generate value.
• Develop strategies for monitoring, drift detection, and version control to ensure continuous high model performance.
• Participate in ongoing improvement efforts to optimize deployment strategies and system robustness.

Qualifications and Skills

• Demonstrated experience in MLOps with practical knowledge of deploying and sustaining ML models in production.
• Advanced proficiency in Python, including software design, testing, and developing production-grade code; extensive experience with scikit-learn pipelines.
• In-depth understanding of the complete ML lifecycle, encompassing data prep, feature engineering, model assessment, monitoring, drift analysis, and version management.
• Experience with data platforms like Snowflake, especially for ML-centric and data-heavy use cases.
• Capability to handle complex IT system environments for robust integration of ML solutions.
• Strong communication skills to articulate technical and business needs collaboratively.
• Self-motivated with a structured approach, taking end-to-end ownership of tasks.
• Familiarity with DevOps tools and processes such as CI/CD and Docker containerization.
• Knowledge of pricing domains like dynamic pricing or price optimization is a plus.
• Fluent English communication.

Benefits

• Flexible work schedules with family-supportive hours and comprehensive home office policies.
• Ergonomic workplace setups and welcoming office environments for on-site workdays.
• Autonomous work culture with quick decision-making channels, promoting innovation and responsibility.
• Annual budget allocation for personal and professional development.
• Vibrant team activities and social engagement opportunities.
• Support for transportation preferences including train passes and parking options.
• Wellness benefits, including discounts on gym memberships and access to fitness centers.
• Financial security programs such as company pension subsidies.
• Customizable perks catering to individual lifestyle requirements.

Equal Opportunity Statement

The company is committed to creating a diverse and inclusive workplace welcoming candidates from all backgrounds, including parents, individuals with disabilities, and LGBTQIA+ community members. Accessible facilities and application support are provided, and accommodations for gender-neutral pronouns or other needs during application and onboarding are encouraged.