Engineering Manager (MLOps) - MoneyLion

At Gen, we are scrappy and relentlessly customer driven. We create room for healthy debate, experimentation and continuous learning, and we seek out people with different experiences, identities and ideas to join our team. You’ll work with people who back each other, respect each other and understand that our differences are a competitive advantage.

If this sounds like you, we’d love you to be part of Gen.

About the Role

The Kuala Lumpur office is the technology powerhouse of MoneyLion. We pride ourselves on innovative initiatives and thrive in a fast paced and challenging environment. Join our multicultural team of visionaries and industry rebels in disrupting the traditional finance industry!

As a Manager for MLOps Engineering, you will have the opportunity to lead and guide the development of the next generation of Moneylion’s machine learning platform and infrastructure. You will lead initiatives to enable the deployment of machine learning solutions at scale. This entails proactively designing, prototyping, and continuously refining the underlying machine learning infrastructure to remove bottlenecks and expedite the modeling lifecycle. You will also help to define, establish, and enforce best practices in partnership with AI Devops, Data Scientists, Data Engineers, and AI Engineers across Moneylion.

Key Responsibilities:

Lead a team of young and bright MLOps Engineers in conducting research, design, and prototype MLOps practices, tools, and frameworks to expedite the machine learning lifecycle at MoneyLion.

Work in collaboration with Data Scientists, Data Engineers, and AI/ML Engineering teams to enhance cross-team workflows and reduce time to deployment.

Improve the level of automation in the development and deployment processes of machine learning.

Collaborate closely with IT operations and DevOps teams to ensure the smooth integration of infrastructure platforms with other applications and processes.

Establish and maintain systems for monitoring machine learning models in production. Oversee the development of machine learning models at MoneyLion to ensure proper model governance.

Effectively manage cloud infrastructure costs by monitoring and optimizing spending, and provide transparency and accountability in cost-related matters.

Develop and implement disaster recovery and business continuity plans for cloud infrastructure platforms.

Responsibility for the dependability of the MLOps platforms and solutions. This entails participating in an on-call rotation to address critical incidents when necessary.

About You:

Strong experiencing managing teams of Software Developers

Strong Software Fundamentals. Experienced with software development standards and best practices on software engineering in an enterprise organization, such as code pattern, code review, test-driven development, unit testing etc

Experience with deploying and managing data pipeline and machine learning algorithms at scale.

Demonstrated practical experience with Kubernetes, with a preference for experience with EKS, in a production environment. In-depth understanding of Kubernetes architecture and its components.

Evaluate and implement best practices and new technologies to enhance application performance, accuracy, and cost efficiency

Proficient in Python, Java, SQL

Strong problem-solving and troubleshooting skills and effective communication and collaboration abilities.

Design and ship applications that provide excellent user experience to data analysts and scientists

Maintain multiple codebases, conduct code reviews or pair programming to ensure high-quality code

Preferably familiar and have experience with MLOps tools such as DVC, MLFlow, Metaflow, Ray, Chalk

What’s Next

TA Screening Call

30-min Chat with our Hiring Managers

Case Study

Final Interview- Hiring Manager (Virtual or face-to-face)

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Gen is an equal opportunity employer, and we’re committed to fair, inclusive practices at every stage of the candidate and employee journey. Employment decisions are based on merit, experience and business needs.