Engineering Manager, Identification Accuracy

📋 Description

• Lead a multidisciplinary ML team to improve identification accuracy at scale.
• Own team roadmap in partnership with engineering leadership and cross-functional stakeholders.
• Guide production ML systems including data pipelines, feature engineering, model training, and
• Foster continuous improvement, experimentation, and data-driven decisions.
• Collaborate with engineering, product, and customer-facing teams to translate customer challenges
• Communicate model performance and roadmap decisions to tech and business audiences.

🎯 Requirements

• Minimum of 2 years leading ML, data science, or engineering teams in agile environments.
• 5+ years of professional software/ML/data science experience.
• Demonstrated success leading teams that build/operate production ML systems.
• Strong understanding of ML workflows: data pipelines, feature engineering, training, evaluation
• Proven ability to mentor and develop high-performing teams.
• Excellent communication to explain complex concepts to diverse audiences.

🎁 Benefits

• Fully remote work environment with location flexibility.
• Opportunity to lead ML, fraud prevention, and digital security projects.
• Competitive compensation based on experience and market conditions.
• Global, distributed team of engineers and data professionals.
• Focus on professional growth, learning, and career development.
• Inclusive, collaborative culture valuing diverse perspectives.