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Open nowFirst seen 2 hours ago

Machine Learning Engineer | Hybrid Setup

HRTX1,659 open roles

Work mode
Hybrid
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Your applicationOpen nowMachine Learning Engineer | Hybrid SetupHRTX

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  2. CV RocketCV written for this posting.

  3. 25 readersRecruiter, hiring manager, skeptic. Round after round.

  4. CV RocketApplied on HRTX's own form.

The reply lands in your private mailbox

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The clock on this job

Early applications get read.

12.3% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.5%3 days
  3. 12.3%7 days
  4. 19.3%14 days
  5. 35.6%30 days
  6. 58.1%60 days
This job: first seen 2 hours ago

The posting

Work Setup: Monday to Friday, Hybrid (2 days onsite, 3 days wfh) Location: Mandaluyong

Key Responsibilities:

  • Develop, implement, and deploy machine learning models to support AI solution development.
  • Optimize machine learning algorithms to enhance performance, efficiency, and scalability.
  • Conduct experiments and evaluate results to improve model accuracy and overall performance.
  • Collaborate with data scientists to prepare datasets and support data preprocessing activities.
  • Monitor and maintain deployed models, document development processes and findings, and stay informed about emerging machine learning techniques and tools.

Qualifications:

  • Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field; a Master’s degree is an advantage.
  • 3–5 years of experience in machine learning and model development.
  • Proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Knowledge of data preprocessing, feature engineering, model evaluation, and optimization techniques.
  • Strong programming skills in Python or R, with familiarity with cloud-based machine learning platforms such as AWS SageMaker or Google AI Platform.
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    The review screen in CV Rocket: how each CV was read, round by round.

  3. We apply on HRTX's form

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  4. Every reply, sorted

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3×

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