Senior Machine Learning Engineer (Causal & Decision Systems)

Location: Hybrid – Costa Rica; an in-person interview at the Costa Rica office is mandatory before an offer.

Company

CSC Generation is an AI-native holding company re-engineering omnichannel retail through its Genesis operating platform, data fabric, automation engine, proprietary tools, and shared services across 13 consumer brands.

What you will do

• Build closed-loop machine learning systems for pricing and future applications in inventory, purchasing, promotions, marketing, and assortment.
• Develop causal and heterogeneous treatment-effect models, uncertainty estimation, contextual bandits, active learning, and sequential decision-making systems.
• Design policy learning, constrained optimization, counterfactual evaluation, and off-policy evaluation methods.
• Build experimentation and champion/challenger systems that evaluate and improve commercial policies.
• Own production ML infrastructure, monitoring, automated deployment, and end-to-end system evaluation.
• Connect model interventions, observed outcomes, and policy updates to generate measurable economic lift in controlled experiments.

Requirements

• Exceptional technical ability and judgment in machine learning and statistical modeling.
• Experience with several of causal inference, experimentation, recommendation or pricing systems, bandits, reinforcement learning, optimization, active learning, uncertainty estimation, counterfactual evaluation, or production ML systems.
• Strong Python and SQL skills and experience working with large behavioral datasets.
• Ability to own problems from framing and modeling through deployment and evaluation.
• Ability to work in a hybrid arrangement in Costa Rica.
• Availability for a mandatory in-person interview at the Costa Rica office before receiving an offer.

Culture & Benefits

• Work on live commercial decisions across a portfolio of consumer brands.
• Technical work at the intersection of causal machine learning, bandit algorithms, and production engineering.
• End-to-end ownership and freedom to select the appropriate method for each problem.
• Primarily remote work within the hybrid role structure.
• Private medical and life insurance, additional paid time off, monthly allowances and reimbursements, employee discounts, and professional growth opportunities.

Hiring process

• Recruiter screen covering background, role details, and mutual fit.
• Virtual interview rounds with the hiring manager and engineering and data science collaborators, covering technical depth, system design, and working style.
• Mandatory in-person interview at the Costa Rica office, followed by reference checks and an offer process.
• A valid LinkedIn profile URL or credible alternative evidence of professional background is required during application.