Senior MLOps Engineer - Remote (PH)

Senior MLOps Engineer

Position Type: Full-Time

Compensation: Up to PHP 137,000

Job Location: Remote

Job Highlights:  

1. High Compensation Tied to Business Outcomes: You will be well-rewarded for meeting critical objectives and deadlines.
2. Empowerment & Resources: We will provide the right tools and teams to help you succeed on your own terms.
3. Flexibility & Accountability: You will have autonomy to structure your approach, but must deliver results.
4. Performance-Based Bonus: Exceptional delivery warrants additional rewards.
5. Paid Time Off: Relax and recharge with paid vacation and sick leaves.
6. Bonus Boost: Enjoy an extra bonus with our 13th month pay.
7. Health Matters: Get comprehensive HMO coverage upon regularization.
8. Work-Ready: We provide the essential work device for seamless productivity.
9. Work From Home: Enjoy the flexibility and convenience of a fully remote position—work from anywhere in the world without ever needing to commute to an office.

Company Overview: 

Theoria Medical is a comprehensive medical group and technology company dedicated to serving patients across the care continuum with an emphasis on post-acute care and primary care. Theoria serves facilities across the United States with a multitude of services to improve the quality of care delivered, refine facility processes, and enhance critical relationships. We offer a broad scope of services including multispecialty physician services, telemedicine, remote patient monitoring, and more. We currently operate primary care clinics and provide medical services to skilled nursing facilities in numerous states across the nation. 

As a leading edge, innovative, and quality driven physician group, we continue to expand nationally.  In pursuit of this, we continue to seek talented individuals to join our amazing team and care for our population. We wish to extend a warm welcome to all candidates interested in making a difference in healthcare delivery by joining the Theoria team.

The Senior MLOps Engineer plays a critical role in designing, implementing, and maintaining scalable and reliable machine learning (ML) operations. This role bridges the gap between data science and operations, ensuring that machine learning models are seamlessly deployed, monitored, and maintained in production environments. The Senior MLOps Engineer will drive automation, efficiency, and governance across the ML lifecycle while collaborating closely with data scientists, DevOps engineers, and other stakeholders.

Shift Structure: 

• TBA

Responsibilities:

• MLOps Implementation and Optimization
• Design, build, and maintain scalable ML workflows and pipelines for model training, deployment, and monitoring.
• Implement automation and version control for ML experiments, datasets, and models.
• Optimize deployment strategies to ensure model scalability, performance, and reliability.
  
  
• Tooling and Infrastructure
• Select and manage MLOps tools and platforms (e.g., MLflow, Kubeflow, SageMaker, Vertex AI).
• Implement and manage model registries, model versioning, and CI/CD for ML workflows.
• Utilize Infrastructure as Code (IaC) to provision and manage ML environments in the cloud or on-premises.
  
  
• Collaboration and Communication
• Collaborate with data scientists to operationalize models from development to production.
• Coordinate with DevOps teams to align ML workflows with broader infrastructure and deployment standards.
• Communicate effectively with stakeholders on MLOps practices, progress, and improvements.
  
  
• Monitoring and Governance
• Develop monitoring and alerting systems for model performance and drift detection.
• Ensure compliance with data privacy, security, and governance standards for ML models in production.

Requirements and Qualifications:

• Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• 5+ years of experience in DevOps, Data Engineering, or Software Engineering, with at least 2+ years focused on MLOps.
• Proficient in Python and experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
• Strong understanding of CI/CD for ML, containerization (Docker, Kubernetes), and cloud platforms (e.g., AWS, Azure, GCP).
• Familiarity with data pipelines, model monitoring, and lifecycle management.
• Hands-on experience with MLflow, Kubeflow, or similar MLOps platforms.
• Experience deploying models in real-time and batch inference settings.
• Understanding of data governance, model explainability, and responsible AI practices.
• Excellent problem-solving, communication, and cross-functional collaboration skills.

Compensation and Benefits:

• 2 rest days per week
• 13th Month Pay

Employee must be able to perform the essential functions of this position satisfactorily, with or without a reasonable accommodation.  Employer retains the right to change or assign other duties to this position.