Sr. Applied Scientist

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Imagine a place where you get the best of both worlds: the speed and energy of a startup, and the experience of leaders who’ve built systems that scale globally. Founded by 23-year Amazon veteran and serial innovator Dave Clark and backed by a $100M investment led by Oak HC/FT, Auger isn’t just rethinking how global supply chains work—we’re redefining them.

Auger is creating the world’s first agentic operating system for supply chains—turning one of the planet’s most complex systems into a source of foresight, resilience, and growth. We partner with leading global enterprises to solve their toughest challenges: accelerating decision speed, reducing costs, unlocking capital, and improving service. With Auger, brittle fragments become an indestructible engine of progress, economic strength, and planetary sustainability.

Supply chain problems aren’t just business problems—they’re human ones. When a supply chain breaks down, products don’t reach shelves, workers face burnout, and the environment pays the price. Auger is here to change that. At Auger, you’ll join an expert team that’s fundamentally reshaping one of the world’s most vital industries. If you’re ready to build technology that makes a real impact on people, business, and the planet—come build with us.

The AI Economics Team at Auger is building an AI and agentic-powered market intelligence system that enables our customers to forecast supply chain risk, optimize sourcing decisions, and respond to global disruptions in real time. We are looking for an Applied Scientist to design, deploy, and scale the systems at the core of this platform.

You will own the end-to-end ML lifecycle for production systems including demand and cost forecasting models, supplier reliability prediction, NLP pipelines for news and document intelligence, and real-time cost calculation engines. Your work will directly inform sourcing recommendations that move billions of dollars in procurement spend. This role sits at the intersection of applied ML and economics research and production engineering.

You will collaborate closely with economists on causal inference methodology, with data engineers on feature pipelines, and with product teams to translate model outputs into actionable customer-facing tools. You should be comfortable shipping models that run at scale, monitoring their performance in production, and iterating based on real-world feedback.

• 4+ years experience building and deploying ML models in production environments
• Strong proficiency in Python and ML frameworks (scikit-learn, XGBoost/Light
  
  GBM, PyTorch)
• Experience with time-series forecasting methods (ARIMA, Prophet, gradient boosting, neural forecasters)
• Familiarity with NLP pipelines: text classification, named entity recognition, document parsing, or sentiment analysis
• Production ML infrastructure: model serving, feature stores, monitoring, retraining workflows, and deployment into existing CI/CD systems(including unit tests and integration tests)
• SQL proficiency and experience with data pipeline tools (Airflow, dbt, or similar)
• Ability to communicate model behavior and limitations to non-technical stakeholders

• Experience with causal ML methods (causal forests, double ML, SHAP-based decomposition)
• Background in supply chain, logistics, trade, or procurement domains
• Familiarity with LLM-based extraction or retrieval-augmented generation (RAG) systems
• Experience with real-time or streaming ML systems
• Graduate degree in computer science, statistics, or a quantitative field

• Highly competitive total compensation packages
• Top tier medical, dental, and vision insurance and wellness perks
• 401K with Company match
• Work with teammates who tackle complex and consequential challenges with resilience, determination, and good humor.

Auger considers all qualified applicants for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.