Software Engineer at Bg Prevent — United States

About The Role

We are looking for an existing Software Engineer - AI Trainer to help train AI models. You'll be part of a growing community of professionals — including front-end, back-end, full-stack, machine learning, and other engineers — who are driving real-world impact in AI development.

Our platform offers an engaging blend of flexibility and challenge: you'll work closely with state-of-the-art AI models to take on programming tasks that include creating and solving challenging coding problems, building beautiful apps with rich functionality, and synthesizing insights through data analysis and visualization. Your work directly contributes to refining intelligent systems that learn, adapt, and evolve. You can fit this work alongside a full-time role, or treat it as your primary focus, choosing projects and schedules that align with your availability and goals.

Responsibilities

Design and solve diverse coding problems used to train AI systems.

Write clear, high-quality code snippets and detailed explanations.

Evaluate AI-generated code for accuracy, performance, and clarity.

Provide feedback that directly shapes the next generation of AI models.

Evaluate AI-generated quantitative work, including statistical analysis, predictive modeling, scientific reasoning, and data-driven insights, for technical accuracy and real-world validity.

Design and solve quantitative problems used to train and benchmark AI systems, spanning areas like forecasting, experimental analysis, optimization, and statistical inference.

Write clear technical explanations and well-documented analytical code.

Provide feedback that directly shapes the next generation of AI models built for quantitative reasoning.

Qualifications

2+ years of hands-on experience in a quantitative role or research environment — such as data science, statistics, economics, finance, physics, biology, epidemiology, operations research, or any adjacent field.

Some coding experience required, with comfort writing and reviewing analytical code end-to-end.

Practical experience with statistical methods, predictive modeling, and experiment design (e.g., A/B testing, hypothesis testing, regression, classification, time-series forecasting).

Fluency in English (native or bilingual level) with strong writing skills.

A bachelor's degree in a quantitative field is preferred (Statistics, Computer Science, Mathematics, Engineering, or similar); a master's or PhD is a plus.

Relevant credentials are a plus (e.g., Kaggle Competition ranking, AWS/GCP ML certifications, or equivalent demonstrated expertise).