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EncoraPosted 1 week ago

Machine Learning Specialist

HybridMakati, Cagayan Valley, Republic of the Philippines

Full TimeMediumTechnology

Job Summary

Conduct deep-dive research into state-of-the-art architectures and foundational models to solve complex business problems in credit scoring, fraud detection, and personalization. Execute rigorous hyperparameter tuning and fine-tuning techniques to maximize model accuracy, while developing evaluation frameworks and leaderboards to monitor performance. Lead the design of experimentation datasets and production data pipelines, ensuring high-quality inputs for training and real-time inference. Architect end-to-end model deployment using containers and CI/CD pipelines, building robust APIs to integrate AI models with internal platforms. Implement MLOps best practices including versioning, drift detection, and automated quality gates. Work as a core member of a cross-functional squad, aligning daily with Data Engineers and Product Owners to translate business requirements into executable research hypotheses. Author technical documentation ranging from scientific findings to deployment guides, while mentoring squad members and conducting code reviews.

Required Qualifications

  • Undergraduate degree in a quantitative field (e.g., Computer Science, Statistics, Information Technology or Physics, or Mathematics)
  • 3+ years in a functionally similar role (Data Science, ML Research, or ML Engineering)
  • Expert-level Python
  • Expert-level SQL
  • Strong experience with ML frameworks (e.g., PyTorch, TensorFlow, JAX)
  • Hands-on experience with Git
  • Hands-on experience with CI/CD
  • Hands-on experience with MLOps tools
  • A strong bias toward model explainability and security
  • 2 x onsite per week hybrid set up

Desired Qualifications

  • A Graduate degree (Master's or PhD) for the research component
  • A demonstrable portfolio of advanced AI use cases (e.g., GenAI, NLP, Recommender Systems, or Graph Algorithms)
  • Familiarity with AWS, GCP, or Azure AI services
  • Published research in relevant AI/ML conferences or journals

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