Design, develop, and implement advanced deep learning models, including transformers, CNNs, and LSTMs, to address complex fraud and risk challenges.
Build and optimize models using a variety of input data types, including tabular data, natural language, point clouds, and images.
Take ownership of assigned tasks, executing technical and functional activities to support project goals with minimal supervision.
Participate in all stages of the machine learning lifecycle: data exploration, feature engineering, model training, evaluation, and deployment.
Collaborate effectively across teams, sharing knowledge and learning from diverse perspectives to drive results.
Make routine technical decisions and contribute to functional objectives through productive and proactive engagement.
Stay current with advancements in AI and machine learning, applying innovative approaches to real-world problems.
Communicate results and insights clearly to both technical and non-technical audiences.

Requirements

Bachelor’s degree with substantial related experience, Master’s degree with relevant experience, or equivalent work background in Computer Science, Statistics, Mathematics, Engineering, or a related field.
2-4 years of hands-on experience developing and deploying deep learning models (such as transformers, CNNs, and LSTMs).
Experience working with diverse data modalities, such as tabular data, text/language, point clouds, and images.
Proficiency in Python and major ML libraries/frameworks (e.g., PyTorch, TensorFlow, scikit-learn).
Foundational understanding of machine learning algorithms, model evaluation techniques, and data pipeline development.
Experience with model deployment and monitoring in production environments (specific experience with real-time model inferencing is a plus)
Experience with LLMs and Agentic AI framework/infrastructure (e.g., LangChain/LangGraph/Ray) is a plus.
Strong problem-solving skills, with the ability to work independently on straightforward tasks and contribute effectively to project objectives.
Demonstrated ability to collaborate in a diverse, cross-functional team environment.
Excellent written and verbal communication skills.
Experience in fraud prevention, risk modeling, or identity verification is a plus.

Benefits

Offers Equity
Offers Bonus

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

deep learning modelstransformersCNNsLSTMsPythonPyTorchTensorFlowscikit-learnmachine learning algorithmsmodel evaluation techniques

Soft Skills

problem-solving skillscollaborationcommunication skillsindependenceproactive engagementownershipknowledge sharingadaptabilityteamworktechnical decision-making