Sluicebox
Artificial Intelligence • eCommerce • Energy
Sluicebox is a leading carbon intelligence platform specifically designed for the electronics industry. Leveraging advanced AI technology, Sluicebox enables companies to accurately scale their carbon footprint assessments across the entire electronics value chain, from initial customer inquiries to comprehensive global product inventories. With features such as real-time eco-design scenario modeling and automated reporting for carbon footprint metrics, Sluicebox aims to optimize emissions reductions and ensure that organizations can achieve efficient and sustainable operations.
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
🛍️ eCommerce
⚡ Energy
Data/ML Engineer
Job not on LinkedIn
August 8
Sluicebox
Artificial Intelligence • eCommerce • Energy
Sluicebox is a leading carbon intelligence platform specifically designed for the electronics industry. Leveraging advanced AI technology, Sluicebox enables companies to accurately scale their carbon footprint assessments across the entire electronics value chain, from initial customer inquiries to comprehensive global product inventories. With features such as real-time eco-design scenario modeling and automated reporting for carbon footprint metrics, Sluicebox aims to optimize emissions reductions and ensure that organizations can achieve efficient and sustainable operations.
11 - 50 employees
Founded 2024
🤖 Artificial Intelligence
🛍️ eCommerce
⚡ Energy
đź“‹ Description
• Join SluiceboxAI as an ML/Data Engineer to build scalable data & ML pipelines that cut emissions. • Own solutions end-to-end. • Work with product and customers, shaping solutions through data and AI. • Build scalable data pipelines, ETL/ELT systems, and model deployment pipelines. • Collaborate with product, engineering, and customers to understand pain points and drive solution design. • Implement automation, data validation, model evaluation, and continuous improvement systems.
🎯 Requirements
• Strong Python experience, particularly in data engineering and/or ML workflows. • Experience building and scaling ETL/ELT pipelines and working with relational databases (PostgreSQL preferred). • Strong understanding of model training, deployment, and monitoring practices. • Product thinking—ability to define solutions, not just execute tickets. • Comfortable with ambiguity, startup pace, and fast problem-solving. • Candidate has to be located in Austria with full-time working rights. • Experience with MLops, vector databases, embeddings, or related fields (nice-to-have). • Exposure to AI/ML model serving (e.g., using FastAPI, TorchServe, TensorFlow Serving) (nice-to-have). • Previous leadership or ownership of high-impact data or ML projects (nice-to-have). • Experience with sustainability, LCA, or environmental data (big bonus, but not required).
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