Machine Learning Specialist

Encora, Makati, Makati, Philippines +1

What you need

Education: Undergraduate degree in a quantitative field (e.g., Computer Science, Statistics,Information Technology or Physics, or Mathematics). A Graduate degree (Master’s or PhD) is highly preferred for the research component.

The following are key areas of responsibility, but not limited to the ff

Research & Experimental Innovation
Advanced Research: Conduct deep-dive research into state-of-the-art (SOTA) architectures and foundational models to solve complex business problems like credit scoring, fraud detection, and personalization.
Model Optimization: Execute rigorous hyperparameter tuning and fine-tuning techniques (e.g., PEFT, LoRA, QLoRA) to maximize model accuracy and efficiency.
Benchmarking & Evaluation: Develop comprehensive evaluation frameworks and leaderboards to monitor model accuracy and compare experimental iterations.
Data Strategy & Engineering
Pipeline Design: Lead the design of experimentation datasets and production data pipelines, focusing on feature engineering and data augmentation.
Data Quality: Ensure high-quality data inputs for both training and real-time inference, collaborating with data squads to maintain data integrity.
Production Engineering & MLOps
Deployment & Orchestration: Architect and manage the end-to-end deployment of models using containers (Docker, Kubernetes) and CI/CD pipelines.
System Integration: Build robust APIs to integrate AI models with internal platforms and refactor research code into production-grade, low-latency, and high-throughput codebases.
Model Governance: Implement MLOps best practices, including versioning (DVC), drift detection, and automated "quality gates" to ensure alignment with internal KPIs and regulatory standards.
Squad Collaboration & Agile Delivery
Active Squad Collaboration: Work as a core member of a cross-functional squad, aligning daily with Data Engineers, Backend Developers, and Product Owners to ensure seamless product integration.
Agile Participation: Drive technical value within Agile ceremonies (Stand-ups, Sprints, Retrospectives) by translating high-level business requirements into executable research hypotheses and production-ready sprints.
Documentation & Knowledge Leadership
Technical Documentation: Author and maintain the full technical stack documentation, ranging from scientific research findings and experimental logs to system architecture diagrams and deployment guides.
Peer Mentoring: Act as a technical subject matter expert by mentoring squad members, conducting code reviews, and fostering an internal culture of AI literacy and "New Ways of Working."

Machine Learning Specialist

What you need

Machine Learning Specialist

What you need

Nice to have

Position Title: Machine Learning Specialist (Research & Engineering)

The following are key areas of responsibility, but not limited to the ff

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Encora