ML Research & Production Engineer

Encora Inc.

Philippines

Hybrid

PHP 1,800,000 - 3,000,000

Full time

5 days ago
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Job summary

Encora Inc. seeks a versatile Machine Learning Specialist to own end-to-end AI development, from research to production-grade pipelines and APIs. You will bridge theoretical innovation with scalable business impact, ensuring robust, cutting-edge AI solutions.

The role involves hands-on work in model research, data engineering, MLOps, and cross-functional collaboration within an agile squad, focusing on explainability and security.

Qualifications

  • Undergraduate degree in a quantitative field; Master’s/PhD preferred for research.
  • 3+ years in DS/ML research/engineering roles.
  • Expert-level Python and SQL.
  • Hands-on with ML frameworks (PyTorch, TensorFlow, JAX).
  • Experience with Git, CI/CD and MLOps tools.
  • Bias toward model explainability and security.

Responsibilities

  • Research & Experimental Innovation: explore SOTA architectures and foundation models.
  • Data Strategy & Engineering: design experiments and production data pipelines; feature engineering.
  • Production Engineering & MLOps: deploy models with Docker/Kubernetes, CI/CD; build robust APIs.
  • Squad Collaboration & Agile Delivery: collaborate with data engineers, backend, product owners; drive agile value.
  • Documentation & Knowledge Leadership: maintain technical docs and mentor squad members.

Skills

Python
SQL
PyTorch
TensorFlow
JAX
Git
CI/CD
MLOps

Education

Bachelor’s degree in CS/Math/IT/Physics
Master’s or PhD preferred

Tools

PyTorch
TensorFlow
JAX
Git
CI/CD tools
MLOps platforms

Job description

Encora Inc. seeks a versatile Machine Learning Specialist to own end-to-end AI development, from research to production-grade pipelines and APIs. You will bridge theoretical innovation with scalable business impact, ensuring robust, cutting-edge AI solutions.

The role involves hands-on work in model research, data engineering, MLOps, and cross-functional collaboration within an agile squad, focusing on explainability and security.

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