About The Company
Remotely is a leading innovator in the financial technology sector, renowned for its commitment to leveraging cutting-edge technology to revolutionize the credit marketplace. As one of the most successful Fintech companies in Germany and the largest credit marketplace in Continental Europe, Remotely connects private and institutional investors directly with pre-approved loans, fostering transparency and efficiency in financial transactions. The company operates with a start-up mentality, emphasizing agility, innovation, and a collaborative work environment while maintaining the stability and security of a well-established organization. With locations in Düsseldorf, Budapest, and Dublin, Remotely prides itself on fostering a diverse and inclusive culture, offering numerous opportunities for professional growth and development. The company values creativity, responsibility, and sustainability, actively encouraging employees to contribute their ideas and expertise to shape the future of financial technology.
About The Role
We are seeking a highly skilled and motivated Machine Learning Engineer to join our dynamic Pricing team. In this role, you will be pivotal in transforming machine learning models into reliable, scalable, and observable production services that directly influence pricing strategies at scale. Your primary focus will be on building and operating systems that power our Dynamic Pricing platform, ensuring models are seamlessly integrated into live environments with high stability and performance. You will collaborate closely with Data Science, Data Infrastructure, and business stakeholders to develop robust technical solutions that meet analytical and operational needs. Your work will involve end-to-end ownership of ML models—from development and training to deployment, monitoring, and continuous improvement. This position offers the flexibility of remote work within Germany or a hybrid setup at our offices in Düsseldorf or Berlin, depending on your preference and team requirements. The role provides an exciting opportunity to shape the technical backbone of our pricing capabilities and make a tangible impact on our business outcomes.
Qualifications
- Proven experience in MLOps, with hands-on expertise in deploying and maintaining machine learning models in production environments.
- Strong proficiency in Python, including software architecture, testing, and building production-quality code, especially with scikit-learn pipelines.
- Comprehensive understanding of the end-to-end ML lifecycle, including data preparation, feature engineering, model evaluation, monitoring, drift detection, and versioning.
- Experience working with data platforms such as Snowflake or similar, particularly in data-intensive and ML-related use cases.
- Ability to navigate complex system landscapes, integrating ML components into existing ecosystems with robustness and reliability.
- Excellent communication skills, capable of translating business and analytical requirements into effective technical solutions and working collaboratively across teams.
- Ownership mindset with a structured, self-driven approach to work, ensuring tasks are completed reliably from start to finish.
- Familiarity with DevOps practices, including CI/CD pipelines and containerization with Docker.
- Optional but advantageous: Knowledge of pricing domains such as dynamic pricing, price optimization, or pricing experimentation.
- Fluent in English, with strong professional communication skills.
Responsibilities
- Take full ownership of machine learning models, overseeing their development, deployment, and ongoing monitoring in production environments.
- Operationalize ML models to ensure stability, maintainability, and scalability, proactively addressing common pitfalls associated with moving from experimentation to production.
- Support and implement training workflows within Snowflake-based environments, facilitating smooth model development and data platform integration across the ML lifecycle.
- Build and enhance applications and services around the Dynamic Pricing System, enabling ML-driven logic within pricing workflows.
- Maintain a comprehensive understanding of complex system landscapes, ensuring seamless integration of ML components with existing infrastructure and data flows.
- Collaborate effectively with Data Science, Data Infrastructure, and business teams to translate requirements into technical solutions that drive business value.
- Develop and implement monitoring, drift detection, and versioning strategies to ensure model performance and reliability over time.
- Contribute to continuous improvement initiatives by optimizing deployment processes and enhancing system robustness.
Benefits
- Flexible working arrangements, including family-friendly hours and a generous home office policy to support work-life balance.
- Ergonomic workstations and a comfortable office environment for on-site days.
- Autonomous working environment with short decision-making pathways, fostering innovation and responsibility.
- Opportunities for professional growth and development, including an annual development budget to pursue personal and career goals.
- Active team culture with regular events and social gatherings to promote camaraderie and team spirit.
- Support for mobility preferences, whether through train tickets or parking allowances.
- Health and wellness benefits, including discounted memberships at Fitness First or Urban Sports Club, and access to on-site fitness facilities.
- Long-term financial security through subsidies for company pension plans.
- Customized benefits tailored to individual needs, whether related to family, travel, or personal interests.
Equal Opportunity
Remotely is committed to fostering an inclusive and diverse work environment. We welcome applications from individuals of all backgrounds, including parents, persons with disabilities, and members of the LGBTQIA+ community. We ensure barrier-free access to our facilities and provide support throughout the application process. Our goal is to create a workplace where everyone feels valued, respected, and empowered to contribute their best. We encourage you to let us know if you require gender-neutral pronouns or any specific accommodations to support your application and onboarding experience.