Engineering Manager, Identification Accuracy

Team: IT

Location: Germany

Commitment: Full-time

Workplace Type: remote

Accountabilities:

As an Engineering Manager, you will lead a specialized team responsible for improving identification accuracy through advanced machine learning solutions. You will balance people leadership, technical direction, and cross-functional collaboration to deliver reliable, scalable, and high-impact products.

• Lead and develop a multidisciplinary team of ML Engineers, Data Scientists, Analysts, and Analytics Engineers, fostering collaboration, psychological safety, and technical excellence.
• Own and drive the team roadmap in partnership with engineering leadership and cross-functional stakeholders, ensuring priorities align with business and customer needs.
• Support the development, evaluation, deployment, and continuous improvement of machine learning models that enhance identification accuracy at scale.
• Guide teams in building reliable production ML systems, including data pipelines, feature engineering processes, model training workflows, and deployment practices.
• Establish a culture of continuous improvement, experimentation, and data-driven decision-making.
• Collaborate with engineering, product, and customer-facing teams to translate customer challenges into technical priorities.
• Communicate model performance, technical tradeoffs, and roadmap decisions clearly to both technical teams and business stakeholders.
• Help create an environment where team members can grow professionally through coaching, feedback, and career development.

Requirements:

The ideal candidate is an experienced engineering leader with a strong background in machine learning, software engineering, or data-driven products. You should have proven experience managing technical teams and delivering production systems in fast-moving environments.

• Minimum of 2 years of experience leading ML, data science, or engineering teams in an agile and rapidly evolving environment.
• 5+ years of professional experience in software engineering, machine learning, data science, or a related technical field.
• Demonstrated experience leading teams that build and operate production machine learning systems.
• Strong understanding of ML development workflows, including data pipelines, feature engineering, model training, evaluation, and deployment.
• Proven ability to build, mentor, and develop high-performing multidisciplinary teams.
• Excellent communication skills with the ability to explain complex technical concepts, model behavior, and data challenges to diverse audiences.
• Experience driving results in scaling environments where priorities shift and ambiguity is common.
• Strong collaboration skills and the ability to work effectively with engineering, product, and business teams.

Preferred Qualifications:

• Experience managing teams working with large-scale behavioral, event, or customer data.
• Familiarity with ML infrastructure and MLOps tools such as experiment tracking platforms, feature stores, model registries, and ML CI/CD pipelines.
• Experience in fraud prevention, identity verification, trust and safety, or related security domains.
• Hands-on experience with analytics engineering tools such as dbt or similar technologies.
• Experience collaborating with platform and API engineering teams on performance, scalability, and reliability requirements.

Benefits:

• Fully remote work environment with flexibility to work from your preferred location.
• Opportunity to lead impactful projects in machine learning, fraud prevention, and digital security.
• Competitive compensation package based on experience, location, and market conditions.
• Opportunity to work with a globally distributed team of talented engineers and data professionals.
• Strong focus on professional growth, learning, and career development.
• Inclusive and collaborative culture that values diverse perspectives and backgrounds.
• Ability to contribute to innovative solutions that improve online trust and security at scale.