About the job
Join Our Team
- As a Machine Learning Engineer at Toss Securities, you will be part of the AI Tribe, collaborating with Data Engineers, Server Engineers, Frontend Engineers, Product Owners, and Product Designers.
- The AI Tribe aims to create data services that provide essential information to investors using data from various securities domains and cutting-edge Machine Learning technologies.
- Our focus is on developing personalized recommendation systems and utilizing LLM-based technologies.
Your Responsibilities
- Develop personalized services based on diverse securities domain data and user behavior data.
- Experiment with reinforcement learning, deep learning, and machine learning methodologies to build recommendation models.
- Formulate and validate hypotheses regarding user information consumption, enhancing our services in the process.
- Define the criteria for recommendations and user profiles beyond simple item suggestions.
Ideal Candidate
- Experience in validating hypotheses through personalization and recommendation systems in real-world applications.
- Strong foundational knowledge of recommendation system domains.
- Hands-on experience experimenting with and optimizing various deep learning and machine learning-based recommendation models.
- Familiarity with modeling based on actual user behavior data from apps.
Resume Tips
- Detail your projects or services, including their objectives and outcomes.
- Focus on impactful projects or services.
- Explain the problems you solved and the technologies you used.
- If certain information is sensitive, please omit those details.
Technologies Used at Toss Securities
- Predict user behaviors through User Modeling based on diverse user data.
- Build deep learning recommendation models by defining and utilizing User Features.
- Implement Multi-Armed Bandit (MAB) technology in our recommendation services.
- Generate and validate data as needed, fine-tuning and testing Large Language Models.
- Conduct experiments and build Retrieval/Chunking/Reranker/Generation models to establish RAG systems.
Application Process
- Application Submission > Job Interview > Cultural Fit Interview > Reference Check > Compensation Negotiation > Final Offer and Onboarding
Important Notes
- Any false information found in your resume or documents may lead to cancellation of your application.
- Individuals prohibited from hiring under Toss Securities regulations may have their applications canceled.
- Disabled individuals and those eligible for national veterans' benefits will be given preference in accordance with relevant laws.
A Message to Future Colleagues
“We are looking for colleagues who are ready to innovate financial services through Machine Learning technology!”
- Investors in the financial market require vast amounts of information to make informed decisions, but knowing what information to seek and where to find it can be challenging.