Applied AI/ML Scientist

Job Summary:

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.

Responsibilities:

• Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
• Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
• Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
• Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
• Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
• Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
• Collaborate with software engineers to productize agentic solutions — including testing, monitoring, versioning, and iterative improvement
• Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

Requirements:

• 4+ years of experience in applied data science or ML in a product environment, with demonstrated experience building agentic systems or autonomous agents
• MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (or equivalent practical experience)
• Proven track record designing and implementing multi-step agentic pipelines, including LLM-based agents, tool use, planning loops, and memory mechanisms
• Hands-on experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or equivalent
• Strong Python coding skills; familiar with Spark for large-scale, distributed data processing
• Experience with LLM APIs (e.g., OpenAI, Anthropic, Bedrock, open-source models) and prompt engineering for agentic use cases
• Experience performing rigorous model evaluation (baselines, cross-validation, error analysis) and defining evaluation strategies for agent behavior
• Strong communication and collaboration skills; able to work across engineering, product, and supply chain domain experts and iterate fast

Nice to Have (Advantages)

• Experience with multi-agent architectures, agent-to-agent communication protocols, and agent orchestration at scale
• Experience with cloud platforms (AWS, GCP, Azure) and MLOps practices (CI/CD for ML, model monitoring, drift detection)
• Familiarity with containerization and production engineering practices (Docker, Kubernetes)