Translate complex business questions into measurable modeling problems and deploy AI-enhanced solutions to production. Build and maintain demand forecasting models, optimization services, and APIs while collaborating with data engineering teams.
We are seeking a highly skilled and experienced Machine Learning Engineer to design, build, and deploy cutting-edge, AI-enhanced applications. You will turn vague business questions into well-defined, measurable modeling problems and take solutions all the way to production.
Key Responsibilities
Translate business questions from planning, operations and sales into modelable problems with clear success metrics.
Build demand forecasting models, including for irregular and sparse demand.
Formulate and solve optimization problems with LP/MIP solvers, and use simulation to test scenarios.
Deploy, version, monitor and retrain models in production, working closely with data engineering.
Build and maintain APIs and services (Python, FastAPI) on a major cloud platform (AWS, Azure or GCP), following security best practices.
Requirements
Solid classical ML and statistics: regression, trees and boosting, regularization, probability and prediction intervals.
Correct validation, including temporal backtesting without data leakage, and metrics tied to business goals.
Time series and demand forecasting, with the judgment to know when a simple baseline beats a complex model.
Operations research: formulating problems as optimization and solving them with Pyomo, OR-Tools, PuLP or similar. Familiarity with Monte Carlo and discrete-event simulation (e.g. SimPy).
Conceptual knowledge of inventory and supply chain: safety stock, service level, lead time, turnover.
Fluent Python for data (pandas, numpy, scikit-learn), advanced SQL, and production-grade backend experience.
Proven experience taking models to production: deployment, monitoring, drift and retraining.
Hands-on experience with a major cloud platform and with API design and backend security basics.
Nice to Have
Databricks, Spark/PySpark; MLOps tooling (MLflow, CI/CD, orchestration, model serving).
ERP data (SAP or similar); BI tools (Tableau, Power BI).
LLM application development (LangChain, LangGraph, OpenAI SDK).
MSc or PhD in Operations Research, Industrial Engineering, Statistics or another quantitative field.
Ambush is a people first company where talented, thoughtful individuals come together to build meaningful products and lasting partnerships. We believe the best work happens when people feel supported, trusted and empowered to bring their full abilities to the table. Since 2015, because of our people first and long term mindset, we have grown into a partner relied on by some of the best companies in the world. We combine strong engineering, design and strategy with a growing strength in AI to help our clients see what is next and achieve bigger outcomes. At the heart of everything we do is our team. We collaborate, take risks, lift each other up and take pride in doing work the right way, not settling for a quick makeshift solution. If you join Ambush, you join a group of people who want you to succeed and who show up for each other every day. We believe in and expect real teamwork, a constant drive to be better, and delivering meaningful long term outcomes that we can be proud of together.
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