Applied AI/ML Scientist

<div class="content-intro"><p><strong data-stringify-type="bold">About Us<br></strong>Beamup helps enterprises move beyond dashboards, alerts, and manual triage to <strong data-stringify-type="bold">automated supply chain execution</strong>.<br>Our AI platform supports large, complex retail and manufacturing networks by deploying specialized AI agents that operate continuously across stores, distribution centers, warehouses, and in-transit operations. These agents detect execution issues, identify root causes, and execute corrective actions - either autonomously or by routing work to the right teams.<br>Retailers and manufacturers rely on Beamup to replace reactive workflows with consistent, scalable execution — reducing losses, improving performance, and operating with greater confidence at global scale.</p> <p><strong data-stringify-type="bold">Our Mission<br></strong>To redefine supply chain intelligence by building AI agents that predict, prevent, and resolve inventory health and operational issues in real time.</p></div><p><strong>Job Summary:</strong></p> <p>We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers. You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.</p> <p><strong>Responsibilities:</strong></p> <ul> <li>Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end</li> <li>Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time</li> <li>Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines</li> <li>Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases</li> <li>Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts</li> <li>Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling</li> <li>Collaborate with software engineers to productize agentic solutions — including testing, monitoring, versioning, and iterative improvement</li> <li>Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing</li> </ul> <p><strong>Requirements:</strong></p> <ul> <li>4+ years of experience in applied data science or ML in a product environment, with demonstrated experience building agentic systems or autonomous agents</li> <li>MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (or equivalent practical experience)</li> <li>Proven track record designing and implementing multi-step agentic pipelines, including LLM-based agents, tool use, planning loops, and memory mechanisms</li> <li>Hands-on experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or equivalent</li> <li>Strong P