Dexter Energy is an Amsterdam-based scale-up dedicated to building AI-based forecasting and optimization products to support renewable energy companies. Our mission is to enable a sustainable and affordable power system that transforms the energy market. We are committed to making a significant impact on climate change by making renewables more predictable and profitable, thus accelerating the transition away from fossil fuels.

Role Overview

We are seeking a highly skilled Software Engineer to join our Machine Learning (ML) Platform team. This role is pivotal in designing and expanding the foundational infrastructure that streamlines the operational machine learning lifecycle and accelerates research and development. Our ML Platform team is seven people: five engineers, a technical product manager and an engineering manager. You will work closely with product teams to enhance model development and release processes, with a focus on quality, auditability, versioning, and data security. Your contributions will ensure that our data processing capabilities, both in batch and real-time streaming environments, are robust and scalable.

Key Responsibilities

• Data Pipeline Development: Build and scale data ingestion pipelines and manage the entire machine learning lifecycle to support the needs of our data scientists and engineers.
• Model Development Support: Enable product teams by providing the necessary tools and processes for model development and release, ensuring high standards of quality, auditability, versioning, and data security.
• Collaboration: Work closely with the Infra team to maintain the availability, reliability, scalability, and maintainability of our ML infrastructure.
• Cross-Functional Communication: Communicate clearly and effectively with team members across different functions and teams, using both verbal and asynchronous channels (e.g. Slack).
• Documentation: Maintain thorough and clear documentation of work processes, decisions, and updates to ensure transparency and knowledge sharing within the team.