Machine Learning Engineer

Beepo; Philippines; Remote; PHP 900,000 - 1,600,000; Full time

Benefits offered by this job

Competitive compensation

Referral program

Equipment provided

Job summary

Beepo is seeking a Machine Learning Engineer to design and implement MLOps infrastructure, enabling teams to experiment quickly and ship confidently. You will build tooling for model versioning, evaluation, monitoring, and automated prompt pipelines, while driving lifecycle practices and production readiness.

Ideal candidates have strong Python engineering skills, production ML experience, and a track record with ML workflows, CI/CD for ML, and cloud services.

Qualifications

• Strong Python engineering skills with production-ready apps.
• Broad experience in ML engineering and deployments.
• Hands-on data/ML pipelines with modern workflows.

Responsibilities

• Design and implement MLOps infrastructure for rapid experimentation.
• Build tooling for model versioning, evaluation, monitoring and feedback.
• Establish structured experimentation and reproducibility processes.
• Automate LLМ prompt pipelines and integrate into production.
• Drive model lifecycle, performance, and production monitoring best practices.
• Mentor peers and promote cross-functional collaboration.

Skills

Python engineering

ML engineering

Data pipelines

Software engineering basics

ML workflows (dev→prod)

MLOps / LLMOps

Model monitoring & experiment tracking

Cloud (AWS / GCP)

Docker

Infrastructure as Code

Production ML deployment

Tools

Docker

AWS

GCP

Job description

Discover 100% YOU as an Machine Learning Engineer

• Position: Machine Learning Engineer
• Location: Central Luzon
• Work setup & shift: Remote | Day Shift

What's in it for you

• Competitive Total Rewards (Compensation, Allowance, HMO, and Paid Time Off)
• Employee Referral Program
• Work Life Balance/Company Provided Equipment

Your Role

As an Machine Learning Engineer, you are responsible for:

• Design and implement MLOps infrastructure so teams can experiment fast and ship with confidence.
• Build tooling for model versioning, evaluation, monitoring and feedback loops.
• Introduce think like a scientist processes — structured experimentation, reproducibility, clear decision frameworks.
• Automate LLM prompt pipelines and integrate them safely and reliably into production systems.
• Drive best practices for model lifecycle management, performance, and monitoring in production.
• Mentor peers in MLOps and engineering best practices; advocate for cross-functional collaboration.

Qualifications, Skills and Experience

• Strong Python engineering skills, with experience developing production-ready applications, services, or ML solutions.
• Broad experience in Machine Learning Engineering, including developing, deploying, and maintaining machine learning solutions.
• Hands-on experience building data and ML pipelines using modern workflow or orchestration frameworks.
• Good understanding of software engineering best practices, including version control, testing, and code quality.
• Experience working with ML workflows from development through deployment and production support.
• Experience with MLOps or LLMOps libraries, tools, and workflows.
• Familiarity with model monitoring, experiment tracking, and ML-focused CI/CD practices.
• Experience working with AWS or GCP data and compute services.
• Experience with containerisation technologies such as Docker.
• Familiarity with Infrastructure as Code (IaC) tools and practices.
• Exposure to deploying and maintaining machine learning models in production environments.

About Beepo

Our Beepo office is located in Clark, Pampanga. We provide exceptional workforce support to clients all over the world. Our primary focus is to help businesses grow sustainably with the help of fantastic Philippine talent.

You will be supported by a great working environment, leading benefits, and an opportunity to meet your career goals. You will be able to apply your skills and innovative thinking to this role. This is an opportunity to grow your career quickly.