Engineering Manager - Identification Accuracy

About the Role

This role is offered by a partner company seeking an Engineering Manager specialized in Identification Accuracy, based in Saudi Arabia. It is a critical leadership position involving the intersection of machine learning, data science, and fraud prevention. You will lead a diverse team responsible for enhancing the accuracy and dependability of a high-impact identification platform. This fully remote role combines the responsibilities of people management, technical strategy formulation, and hands-on execution within a globally dispersed team.

You will define the team's roadmap and supervise the development of production-grade ML systems that operate at an immense scale. Collaborating closely with engineering, product, and customer teams, you'll convert business requirements into actionable technical goals, contributing significantly to top-tier fraud detection technology.

Key Responsibilities

• Lead and expand a multidisciplinary Identification Accuracy group comprising ML engineers, data scientists, analysts, and analytics engineers while promoting psychological safety, technical excellence, accountability, and ongoing improvement.
• Partner with senior engineering leads and stakeholders to establish the team’s technical roadmap, focusing on model quality improvements and addressing complex identification problems.
• Ensure measurable improvements in model accuracy by guiding the team in designing, evaluating, training, and deploying machine learning models affecting billions of devices.
• Oversee the development and delivery of scalable, reliable production ML systems covering data pipelines, feature engineering, and model lifecycle from evaluation to deployment.
• Collaborate with platform and API teams to understand performance requirements and latency constraints downstream.
• Work with Product and customer-facing units to align customer needs and business priorities with technical initiatives and product developments.
• Articulate model performance metrics, data quality issues, trade-offs, risks, and roadmap updates clearly to both technical peers and senior business stakeholders.
• Cultivate a high-performing multidisciplinary team by mentoring, fostering leadership development, and establishing a workspace that empowers excellence.
• Drive continuous improvement in engineering and ML practices, including experimentation methodologies, model validation, MLOps workflows, data handling, and operational efficiencies.

Qualifications and Requirements

• Minimum of 5 years in professional software engineering, machine learning, data science, or related fields, including at least 2 years managing ML or data science teams in dynamic, fast-moving environments.
• Proven track record leading technical teams delivering production-level machine learning systems encompassing data pipelines, feature engineering, model training, evaluation, and deployment.
• Experience developing high-performing, multidisciplinary groups including engineers, data scientists, and analysts.
• Solid understanding of machine learning principles, data systems, and MLOps tools such as experiment tracking, feature stores, model registries, and continuous integration/deployment pipelines for ML.
• Proficiency handling large-scale behavioral or event data in a production context.
• Hands-on experience with data stack and analytics engineering tools like dbt or equivalents.
• Ability to collaborate effectively with platform and API engineering teams while comprehending technical requirements, system dependencies, and latency considerations.
• Exceptional written and verbal communication skills to simplify complex model behaviors, data quality challenges, and technical trade-offs for diverse audiences.
• Track record of delivering impactful results in rapidly evolving environments characterized by shifting priorities and uncertainty.
• Strong leadership skills, including coaching, mentorship, development, and nurturing a culture that promotes psychological safety and high performance.
• Experience relevant to fraud detection, identity management, trust & safety or similar domains is advantageous but not mandatory.
• Authorized to work from Poland; no visa sponsorship available.

Benefits

• Competitive salary package, with US-based roles earning between $159,000 and $215,000 USD annually, and compensation for Poland and other locales aligned with local market standards.
• Fully remote working setup within an international team.
• Leadership opportunity over a multidisciplinary ML and data science team tackling complex challenges at scale.
• Access to advanced machine learning, fraud detection, identity verification, and data technologies.
• Significant autonomy and influence over technical direction, team growth, and product success.
• Inclusive culture appreciating diverse experiences and viewpoints.
• Work on technology that supports major enterprises and expanding companies worldwide.

Additional Information

This vacancy is managed through an AI-driven candidate matching process designed to review applications efficiently and impartially according to core requirements. The partner company handles all subsequent interview stages and decisions.

Applicants agree to personal data processing under applicable privacy regulations. AI tools may assist the recruitment team but do not determine final hiring decisions. Queries about data handling are welcomed.