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.
Data and ML Engineer
Job not on LinkedIn
September 4
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.
📋 Description
• Build scalable data pipelines, ETL/ELT systems, and model deployment pipelines • Own the design, development, and optimization of ML workflows and databases • Work across the stack—primarily back-end and data engineering, with occasional front-end contributions • Collaborate with product, engineering, and customers to deeply understand pain points and drive solution design • Implement automation, data validation, model evaluation, and continuous improvement systems • Optionally explore cutting-edge ML techniques for document parsing, carbon estimation, and system optimization • Own solutions end-to-end and help shape how the company solves complex industry problems through data and AI
🎯 Requirements
• Strong Python experience, particularly in data engineering and/or ML workflows • Experience building and scaling ETL/ELT pipelines • Experience 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 • Nice-to-Haves: Experience with MLOps, vector databases, embeddings • Nice-to-Haves: Exposure to AI/ML model serving (e.g., FastAPI, TorchServe, TensorFlow Serving) • Nice-to-Haves: Previous leadership or ownership of high-impact data or ML projects • Nice-to-Haves: Experience with sustainability, LCA, or environmental data (big bonus)
🏖️ Benefits
• Remote work (must be based in Austria) • Relocation support (Austria) • Work directly with leadership and ownership of work • Minimal red tape; fast impact • Opportunity to shape technical foundation and grow with company • Mission-driven work reducing emissions via automated LCA
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