ML/AI, Supply Chain

This is a fully remote position, open to applicants in United States, +1 more country.

📋 Description

• Develop a comprehensive AI transformation roadmap for the supply chain in collaboration with the Senior Director of Supply Chain AI Transformation.

• Design, train, validate, and implement machine learning models for production, focusing on demand forecasting, inventory optimization, supplier risk assessment, cellular spending predictions, and hardware cash flow.

• Create predictive models addressing demand, inventory, lead times, and expenditure throughout the global supply network.

• Generate features from extensive ERP, IoT, and external datasets.

• Construct pipelines and ETL processes to support models and stakeholder needs.

• Produce production-grade code capable of supporting both batch and real-time inference.

• Serve as the AI representative for Product, Engineering, Procurement, and Finance teams.

• Improve data infrastructure and analytics platforms to facilitate real-time model training, monitoring, and scaling inference.

• Guide junior scientists through code reviews and collaborative projects.

• Act as a scientific authority in roadmap planning, experimentation frameworks, and modeling strategies.

• Identify deficiencies in data, tools, and processes, leading initiatives to address them.

• Establish governance frameworks, documentation standards, and quality controls for model development, validation, and lifecycle management.

• Collaborate with Operations management to promote the adoption of AI tools and train supply chain teams on workflows driven by insights.

• Define the team’s roadmap, scientific agenda, and modeling standards.

• Work alongside Planning, Procurement, Fulfillment, Finance, Sales, and hardware, firmware, and quality engineering teams.

• Create models utilizing ERP data, IoT telemetry, market intelligence, and operational metrics to enhance supply chain efficiency.

⛳️ Requirements

• Over 8 years of experience in applied data science or machine learning, preferably in supply chain, operations research, logistics, or manufacturing.

• Master's or PhD in Computer Science, Statistics, Data Science, Electrical Engineering, Operations Research, or a closely related technical field.

• Proficiency in statistical modeling and machine learning, including time series forecasting, optimization, anomaly detection, and causal inference.

• Strong skills in Python programming and fluency in SQL.

• Demonstrated experience in developing and deploying production-level machine learning systems.

• Knowledge of MLOps practices, including automated testing, CI/CD, model versioning, monitoring, and performance tracking.

• Experience in building real-time inference pipelines.

• Familiarity with managing GPU/TPU resources for large-scale training.

• Experience with tools such as Tableau, Power BI, AWS, GCP, and Azure.

• A strong commitment to operational excellence, cost efficiency, and scalable solutions.

• Proven ability to take products or systems from conception to execution.

• Outstanding problem-solving, critical thinking, and communication abilities.

• History of cross-functional collaboration and promoting data-driven solutions.

• Capability to design and validate A/B tests and multi-armed bandit experiments.

• Experience with Bayesian methods for uncertainty quantification.

• Experience in developing advanced forecasting models like Prophet, LSTMs, or Transformer-based models.

• Knowledge of ML workload profiling, model compression, quantization, pruning, and serverless architectures.

• Ability to deploy low-latency inference across various geographic regions with failover and disaster recovery strategies.

• Experience in evaluating and integrating third-party machine learning platforms.

• Contributions to or utilization of relevant open-source projects.

• In-depth understanding of supply chain concepts such as S&OP, IBP, safety stock, and EOQ.

• Familiarity with ERP systems like SAP, NetSuite, E2DP, and Propel.

• Knowledge of inventory optimization theory.

• An ideal background in consumer electronics or B2B hardware manufacturing.

🏝️ Benefits

• Initial RSU grant with no vesting cliff.

• Continuous equity refresh opportunities linked to performance.

• Performance-based bonus or variable pay.

• Equity for qualifying roles.

• Flexible, employee-driven remote work model.

• Professional development stipend.

• Comprehensive health insurance plans.

• Parental leave policies.

• Flexible working arrangements.

• Support for remote work.

• Option for in-person office work.