Machine Learning Ops Engineer

About us

We're a financial services company leveraging cutting-edge technology to provide fintech and financial solutions to the underserved Southeast Asia market. Our team is a diverse and carefully selected group of finance and tech professionals worldwide.With the successful launch of our first product. Our top-tier international talent, based in Bangkok, continues to innovate and drive forward in our fast-paced and quality-driven environment.
Our journey is marked by continuous learning, growth, and a passion for our work. We remain committed to breaking new ground, adapting, and thriving amidst the challenges and opportunities that lie ahead.

Who You Are

A detail-oriented and experienced technical engineer. You know that data is gold, and you treat it as such. You want to keep it safe, know how much there is, where it came from, how to safely distribute it to those that need it, and when to use alchemy to enrich it further. As a team player, you know when to ask for help and when to lend it too. Not in Bangkok? No worries, we’ll get you here!

What You’ll Do

You will bridge the gap between data science and IT operations, ensuring machine learning models are deployed, monitored, and maintained in production environments. You will automate the entire ML lifecycle, from training to deployment, and monitor model performance to ensure reliability and scalability. This role also involves collaborating with data scientists and other teams to integrate models into existing workflows.

You’ll help us

• Manage the deployment and operation of models leveraging both streaming and batch processing.
• Delve into diverse technologies, including ML models, big data, and MLOps infrastructure, Kubernetes to ensure seamless integration and performance.
• Write design documentation for your solution.
• Write testable, modular, maintainable code. Ensure your code is extensively tested and complies with common standards. Perform code reviews.
• Design and support an internal ML platform to increase data science team velocity and reduce time-to-production.
• Monitor ML models in production and help stakeholders diagnose training/ serving skew.
• Implement and support data pipelines and model versioning policies.
• Expect to be on call for incident resolution.
• Collaborate with data scientists to support model development.

With These, You’re Likely to Succeed

• 3+ years working in a position of MLOps Engineer.
• Experience with Data warehouses (BigQuery) and ELT tools (DBT)
• Experience with Workflow Management tools (Dagster, Airflow)
• You excel in architecting and maintaining robust systems that ensure high uptime and reliability for machine learning pipelines and data pipelines.
• Experience in designing highly scalable models and feature storage, training, and serving infrastructure.
• Strong Python coding and testing skills and experience with common frameworks such as Pydantic, Poetry, Python linters, and type checkers.
• Experience writing and releasing Python packages via a GitOps CI/CD pipeline.
• Experience with ML common frameworks such as scikit-learn, any of the popular boosting frameworks (LightGBM, XGBoost, CatBoost).
• You know how to manage dependencies and ensure consistent environments, best practices for containerizing and deploying an ML solution (e.g., Docker and Kubernetes).
• Experience with both offline batch and online model deployment.
• Familiarity with one of the common cloud providers and experience with ML/ data cloud services, specifically (preferably GCP).
• Experience with or willingness to adopt Infrastructure-as-Code paradigms and frameworks (e.g., Terraform).
• Collaboration is second nature to you, knowing when to collaborate and when to lead in optimizing ML operations.
• Demonstrate exceptional verbal and written communication skills in English.

Bonus Points

• Experience in financial services, e-commerce, credit, or another high-volume, low-latency environment.
• Exposure to modern open-source and/or cloud provider ML platforms.
• Fluency in Thai and/or Bahasa.

About working with us

• This position is based in our Bangkok office
• We prefer to collaborate in person and don’t offer remote work
• As an international team, English language proficiency is required

Our application process

Hiring is something we do with care. Because of that, we believe that having a transparent and thorough recruitment process is key. If you liked what you've read and are up for the challenge, here is what to expect after submitting your resume:

1. The hiring team reviews your application
2. You get invited to an initial call with the hiring team
3. On-site or remote interviews with relevant team members
4. Offer

Why You'll Love It Here

• We’re all owners; Everyone at Honest gets ESOP (Employee Stock Option Plan)
• Training Course and Book Subsidies
• You’ll be working with the smartest people in the industry
• A modern office right in the heart of Bangkok
• A medical healthcare plan
• Monthly Wellness Allowance
• One of the best-funded startups in Southeast Asia with Silicon Valley and Japanese investors
• We don’t believe in titles or hierarchy, but value contribution & celebrate achievements as a team

Honest Hiring

At Honest, we’re working hard to build the future of finance for Asia. To achieve this, we prioritize attracting the best talent from around the world to join us – regardless of their background or heritage.
At Honest, we are committed to equal employment opportunity regardless of race, color, ethnicity, ancestry, religion, national origin, gender, sex, gender identity or expression, sexual orientation, age, citizenship, marital or parental status, disability, or other class protected by applicable law. We are proud to be an equal opportunity workplace.
If you want to be part of changing how people access finance in Asia, come join us and help us build a global company where we’re all proud to belong.