Machine Learning Engineer
Job Description
About the Position
The Kuala Lumpur office serves as the technological hub of MoneyLion, where we take pride in our innovative projects and excel in a dynamic and competitive atmosphere. Join our diverse team of forward-thinkers and disruptors as we challenge the conventional finance landscape!
We are in search of a Machine Learning Engineer who possesses a solid programming foundation to develop machine learning systems and ensure the efficiency of high-performing models in production. As a machine learning engineer, you will be tasked with framing business challenges and crafting machine learning solutions that deliver tangible value to the organization. Your responsibilities will include prototyping, implementing, and experimenting with various machine learning techniques to address business needs. You will spearhead initiatives to automate, design, and enhance machine learning processes and workflows, while also helping to establish, implement, and uphold best practices for test-driven model development within the entire Data Science team at MoneyLion.
Primary Responsibilities
- Frame and contextualize machine learning challenges
- Conduct research, and design machine learning systems and models to tackle business issues
- Evaluate, comprehend, and analyze data to choose suitable datasets for modeling and testing
- Identify, prototype, and apply relevant machine learning algorithms and tools to enhance our products
- Design, execute, and oversee experiments and metrics for machine learning models
- Perform statistical analyses to assess and validate the business impact of modeling enhancements
- Automate, design, and orchestrate machine learning processes and pipelines
- Monitor, optimize, and sustain machine learning solutions in a production environment
- Enhance existing machine learning libraries and model development frameworks to support model creation at MoneyLion
- Collaborate with MLOps Engineers and Data Scientists to refine system designs and architectures
- Promote test-driven development and advocate for engineering best practices to mitigate technical debt in machine learning systems
- Develop tools and internal libraries to support model governance throughout the machine learning development lifecycle
About You
- Strong background in mathematics, statistics, or actuarial science
- Solid programming knowledge and software engineering capabilities
- Hands-on experience with machine learning, predictive analytics, and statistical modeling
- Experience in developing and deploying machine learning models in a production setting
- Adept at problem-solving and troubleshooting using traditional methods as well as innovative approaches
- Proficient in Python and SQL
- Familiar with machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM
- Preferably experienced in building machine learning systems and workflows
- Preferably knowledgeable about MLOps tools like DVC, MLFlow, Metaflow, Seldon, BentoML
- Preferably experienced with AWS, Docker, and Kubernetes
- Excellent communication and collaboration skills
Next Steps...
Upon submitting your application, you can anticipate the following stages in our recruitment process:
- Online Technical Assessment
- Take-Home Task
- Interview & Discussion regarding Take-Home Task - Hiring Manager (Virtual or in-person)
If you have previously applied for this role and were not selected, we encourage you to reapply after 6 months.
Our Core Values
We value individuals who are growth-oriented and collaborative, possessing high learning agility, and who embody our fundamental principles of teamwork, a customer-first approach, and innovation. Every member of the MoneyLion Team is passionate about fintech and dedicated to contributing fully to our mission.
MoneyLion is committed to ensuring equal employment opportunities for all staff members. All decisions regarding our employees are based solely on merit, competence, and performance, without any form of discrimination. We strive to build a team that reflects a variety of backgrounds, perspectives, and skills. Within this team, everyone is valued equally, and we are committed to realizing the full potential of diversity, encouraging you to bring your authentic self to work every day.