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Lead ML Engineer

Discussion
  • Architect and lead the development of large-scale ML systems and model pipelines
  • Introduce new ML systems such as traffic sign detection, building facade detection, and other computer vision-based solutions
  • Define and drive the ML technical roadmap in alignment with company objectives
  • Act as a technical mentor and leader for other ML engineers
  • Facilitate cross-team collaboration with product, engineering, and domain experts
  • Ensure engineering excellence through robust review processes, documentation, and technical standards
  • Own and refine deployment processes for real-time and batch ML services
  • Evaluate emerging tools, techniques, and architectures and apply them strategically
  • Support technical decision-making across ML architecture, data pipelines, model development, and deployment
  • 5+ years of experience in ML/AI with a strong focus on production-grade computer vision and deep learning models
  • Expert-level Python and PyTorch skills
  • Deep knowledge of scalable ML systems, data lifecycle management, and MLOps practices
  • Proven technical leadership experience including mentoring engineers, leading projects, or guiding ML teams
  • Strong architectural thinking and the ability to make pragmatic technical decisions
  • Strategic thinking and excellent communication skills
  • Passion for sustainability and real-world applications of ML
  • Experience with complex algorithms and large-scale data processing
  • Experience in managing, mentoring, or helping build small ML teams
  • Experience with remote sensing, GIS, LiDAR, or point cloud data
  • Experience with workflow orchestration tools such as Airflow
  • Experience with DevOps practices and tools including Docker and Kubernetes
  • Experience with cloud ML environments especially Azure
  • Experience with technical hiring, interviewing, and team scaling
  • Direct impact on climate adaptation and the future of cities through technology that actually gets used
  • Work on meaningful, real-world problems at the intersection of AI, sustainability, and urban tech
  • Join a fast-growing, international team with real freedom to shape both the product and your role
  • Learn, experiment, and grow with talented, curious (green-)tech experts who genuinely care about what they build
  • Continuous development with access to LinkedIn Learning and hands-on learning every day
  • Work 4 days a week from the office with 1 day from home creating space for collaboration while still keeping some freedom
  • Shower
  • Corporate events
  • Bicycle storage
  • Sports facilities
  • Dog friendly

See also

ML / AI jobs by country — openings, pay and top skills →

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