Senior Machine Learning Engineer
MYS - Kuala Lumpur · Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Product & Portfolio — team source
Department: Product & Portfolio
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you now or in the future require employment visa sponsorship to work in the country in which the job you're applying for is located?
From the employer’s application form
What you’ll work on
Full postingThe Kuala Lumpur office is the technology powerhouse of MoneyLion.
We are looking for a Machine Learning Engineer who is technically proficient in programming to build machine learning systems and maintain high performing machine learning models in production.
Own architecture, orchestration and delivery of ML systems and pipelines
Design, run and monitor model experiments and metrics
Monitor, optimise and maintain ML solutions in production
Champion test-driven development and engineering best practices
Mentor junior ML engineers through guidance and code review
From the employer’s posting
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!
We are looking for a Machine Learning Engineer who is technically proficient in programming to build machine learning systems and maintain high performing machine learning models in production. Designing machine learning systems requires that you, as the machine learning engineer, is able to frame business problems and design machine learning solutions that can effectively bring value to the company. You will prototype, implement and experiment with machine learning methods to solve business use cases. You will lead efforts to automate, architect and optimise machine learning processes and workflows. You will also help define, execute and enforce best practices for test-driven model development processes for the entire Data Science team in MoneyLion.
Own and lead the end-to-end architecture, orchestration, and delivery of machine learning systems and pipelines
Design, execute and monitor machine learning model experiments and metrics
Monitor, optimise and maintain machine learning solutions in production
Champion and enforce test-driven development and engineering best practices
Mentor junior ML engineers, providing guidance, code review feedback, and supporting their technical growth
What you’ll bring
All qualificationsCore experience
- Proven track record deploying and owning ML models in production at scale
- Proficient in Python and SQL
- Solid experience building ML systems, workflows and pipelines end-to-end
- Hands-on experience with AWS, Docker, Kubernetes
- Strong communication and stakeholder management skills
Preferred experience
- Proficient with machine learning libraries and frameworks; hands-on experience with tools such as scikit-learn, XGBoost, or LightGBM is preferred
Qualification wording
Proven track record of developing, deploying and owning machine learning models in production at scale
Proficient in Python and SQL
Solid experience building machine learning systems, workflows and pipelines end-to-end
Hands-on experience with AWS, Docker, Kubernetes
Strong communication, collaboration, and stakeholder management skills
Proficient with machine learning libraries and frameworks; hands-on experience with tools such as scikit-learn, XGBoost, or LightGBM is preferred
Tools in this posting
- Python
- SQL
- AWS
- Docker
- Kubernetes
- MLflow
- LightGBM
- scikit-learn
- XGBoost
Source — Tool mentions in context
- Adept at problem solving and troubleshooting using both textbook methods and novel viewpoints; able to navigate ambiguity independently - Proficient in Python and SQL - Proficient with machine learning libraries and frameworks; hands-on experience with tools such as scikit-learn, XGBoost, or LightGBM is preferred
- Familiarity with MLOps tools such as DVC, MLFlow, Metaflow, Seldon, or BentoML is a strong advantage - Hands-on experience with AWS, Docker, Kubernetes - Strong communication, collaboration, and stakeholder management skills
- Solid experience building machine learning systems, workflows and pipelines end-to-end - Familiarity with MLOps tools such as DVC, MLFlow, Metaflow, Seldon, or BentoML is a strong advantage - Hands-on experience with AWS, Docker, Kubernetes
- Proficient in Python and SQL - Proficient with machine learning libraries and frameworks; hands-on experience with tools such as scikit-learn, XGBoost, or LightGBM is preferred - Solid experience building machine learning systems, workflows and pipelines end-to-end
Posting record
Report an errorOpen 4 monthsWe first saw this listing 120 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 24, 2026 · 120 days ago
- Recorded sightings
- 192
- Last seen by us
- Oct 22, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
Your next step
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Job description
About Gen
Gen is a global company dedicated to powering Digital Freedom through its trusted consumer brands including Norton, Avast, LifeLock, MoneyLion and more. Our combined heritage is rooted in financial empowerment and cyber safety for the first digital generations, and today we deliver award-winning cybersecurity, online privacy, identity protection and financial wellness solutions to nearly 500 million users in more than 150 countries.
Together, we share a collective passion and vision to protect consumers and help them grow, manage and secure their digital and financial lives. We’re always looking for smart, fearless and high-impact talent who see AI as a teammate – leveraging it to move faster and deliver meaningful results.
When you’re part of Gen, you’ll have the flexibility, tools and support to do your best work and grow your career – from flexible working options and time off to competitive pay, benefits and well-being programs.
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!
We are looking for a Machine Learning Engineer who is technically proficient in programming to build machine learning systems and maintain high performing machine learning models in production. Designing machine learning systems requires that you, as the machine learning engineer, is able to frame business problems and design machine learning solutions that can effectively bring value to the company. You will prototype, implement and experiment with machine learning methods to solve business use cases. You will lead efforts to automate, architect and optimise machine learning processes and workflows. You will also help define, execute and enforce best practices for test-driven model development processes for the entire Data Science team in MoneyLion.
Key Responsibilities
Own and lead the end-to-end architecture, orchestration, and delivery of machine learning systems and pipelines, from problem framing to production
Lead technical discussions with MLOps Engineers and Data Scientists to drive sound system design decisions
Research, build and design robust, scalable machine learning systems and models that deliver measurable business value
Design, execute and monitor machine learning model experiments and metrics; drive conclusions and recommendations independently
Monitor, optimise and maintain machine learning solutions in production; proactively identify and resolve systemic issues
Champion and enforce test-driven development and engineering best practices to reduce technical debt across ML systems
Mentor junior ML engineers, providing guidance, code review feedback, and supporting their technical growth
About YouProven track record of developing, deploying and owning machine learning models in production at scale
Adept at problem solving and troubleshooting using both textbook methods and novel viewpoints; able to navigate ambiguity independently
Proficient in Python and SQL
Proficient with machine learning libraries and frameworks; hands-on experience with tools such as scikit-learn, XGBoost, or LightGBM is preferred
Solid experience building machine learning systems, workflows and pipelines end-to-end
Familiarity with MLOps tools such as DVC, MLFlow, Metaflow, Seldon, or BentoML is a strong advantage
Hands-on experience with AWS, Docker, Kubernetes
Strong communication, collaboration, and stakeholder management skills
Demonstrated ability to mentor others and contribute to team-wide engineering culture
What’s Next
TA Screening Call
Take-Home Assessment
Interview & discussion of Take-Home Assessment with the Hiring Manager (F2F)
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
No pay amount identified in the saved description.
- Location & working pattern
Kuala Lumpur, Wilayah Persekutuan Kuala Lumpur, Malaysia
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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