this position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a engineering manager, identification accuracy based in mexico.

this is a high-impact engineering leadership role at the intersection of machine learning, data science, and fraud prevention. You will lead a multidisciplinary team responsible for improving the accuracy and reliability of a critical identification platform. The role combines people leadership, technical strategy, and hands-on program direction in a globally distributed, fully remote environment. You’ll shape the team roadmap and guide the development of production ml systems operating at massive scale. Working closely with engineering, product, and customer-facing teams, you’ll translate business needs into meaningful technical priorities. This is an opportunity to influence both the technology and the people behind a best-in-class fraud detection capability.

accountabilities

- lead and grow a multidisciplinary identification accuracy team spanning ml engineers, data scientists, analysts, and analytics engineers, fostering psychological safety, technical excellence, accountability, and continuous improvement.
- own the team’s technical roadmap in collaboration with senior engineering leadership and cross-functional stakeholders, identifying opportunities to improve model quality and address complex identification challenges.
- drive measurable model accuracy outcomes by enabling the team to design, train, evaluate, and deploy machine learning models that improve identification performance across billions of devices.
- oversee the delivery of production ml systems across data pipelines, feature engineering, model development, evaluation, and deployment, ensuring reliability and scalability.
- partner closely with platform and api engineering teams to understand downstream requirements, performance expectations,



and latency constraints.
- collaborate with product and customer-facing teams to translate customer needs and business priorities into technical initiatives and product improvements.
- communicate model performance, data-quality considerations, technical trade-offs, risks, and roadmap priorities clearly to both technical teams and senior business stakeholders.
- build a high-performing, multidisciplinary organization by mentoring team members, developing technical leaders, and creating an environment where people can do their best work.
- continuously improve engineering and ml practices, including experimentation, model evaluation, mlops, data workflows, and operational processes.

requirements

- 5+ years of professional experience in software engineering, machine learning, data science, or a related technical discipline, including at least 2 years leading an ml or data science team in a fast-paced environment.
- proven experience managing technical teams that deliver production machine learning systems, from data pipelines and feature engineering through model training, evaluation, and deployment.
- demonstrated success building and developing high-performing multidisciplinary teams that include engineers, data scientists, analysts, or analytics engineers.
- strong technical understanding of machine learning and data systems, with familiarity with mlops practices and tooling such as experiment tracking, feature stores, model registries, and ml ci/cd pipelines.




- experience working with large-scale behavioral or event data in production environments.
- hands-on familiarity with data stack and analytics engineering technologies such as dbt or similar tools.
- ability to work effectively with platform and api engineering teams and understand technical requirements, system dependencies, and latency constraints.
- excellent written and verbal communication skills, with the ability to translate complex model behavior, data-quality challenges, and technical trade-offs for both technical and non-technical audiences.
- demonstrated ability to deliver results in rapidly scaling environments where priorities evolve and ambiguity is part of the work.
- strong people leadership skills, including coaching, mentoring, team development, and fostering a culture of psychological safety and high performance.
- experience in fraud detection, identity, trust & safety, or a related domain is a plus, but not required.
- must be authorized to work from poland; visa sponsorship is not available for this role.

benefits

- competitive compensation package; for us-based employees, the stated cash compensation range is $159,000–$215,000 usd , while compensation for poland and other locations may vary according to local market benchmarks.
- fully remote work environment with a globally distributed team.
- opportunity to lead a multidisciplinary ml and data organization solving challenging problems at significant scale.
- exposure to cutting-edge machine learning, fraud detection, identity, and data technologies.
- high level of autonomy and meaningful influence over technical strategy, team development, and product outcomes.
- inclusive environment that values diverse experiences, perspectives, and backgrounds.
- opportunity to work on technology used by major enterprises and high-growth companies worldwide.

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📌 Engineering manager, identification accuracy (México)
🏢 Jobgether
📍 México