Remote Engineering Manager, Identification Accuracy & ML

Jobgether; Portugal; Teletrabalho; EUR 159 000 - 215 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Fully remote work environment

Global team collaboration

Leadership in ML & data organization

Exposure to cutting-edge ML tech

Resumo da oferta

Jobgether is seeking an Engineering Manager for Identification Accuracy to lead a global, fully remote team of ML engineers and data scientists. You will shape the roadmap, drive model improvements, and guide production ML systems across data pipelines, feature engineering, and deployment.

You will partner with product and customer teams to translate business needs into technical initiatives, mentor leaders, and elevate practices in MLOps, experimentation, and data workflows.

Qualificações

• 5+ years in software/ML, with 2+ years leading ML teams in fast-paced settings.
• Experience delivering production ML systems from data pipelines to deployment.
• Proven ability to build high-performing, multi-disciplinary teams.

Responsabilidades

• Lead a multidisciplinary Identification Accuracy team of ML engineers and data scientists.
• Own the team's technical roadmap with cross-functional stakeholders.
• Drive model quality improvements and scalable production ML systems.
• Oversee data pipelines, feature engineering, and ML model deployment.
• Collaborate with product and customer-facing teams to align tech initiatives with business needs.
• Mentor and develop engineering leaders and foster psychological safety.
• Advance ML practices, including MLOps, experimentation, and data workflows.

Conhecimentos

Team leadership

ML engineering

Data science

MLOps

Communication

Strategic planning

Formação académica

Bachelor’s degree or higher in a relevant field

Ferramentas

dbt

Descrição da oferta de emprego

Jobgether is seeking an Engineering Manager for Identification Accuracy to lead a global, fully remote team of ML engineers and data scientists. You will shape the roadmap, drive model improvements, and guide production ML systems across data pipelines, feature engineering, and deployment.

You will partner with product and customer teams to translate business needs into technical initiatives, mentor leaders, and elevate practices in MLOps, experimentation, and data workflows.