Role overview

Machine Learning Engineer- Expert

Requirements and responsibilities

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Role Responsibilities

  • Develop end-to-end machine learning solutions for challenging prediction and modeling problems.
  • Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics.
  • Perform exploratory data analysis, feature engineering, and data preprocessing.
  • Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets.
  • Review and validate the technical quality of machine learning projects and deliverables.
  • Identify opportunities to improve model performance through systematic experimentation and iteration.

QualificationsMust-Have

  • Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university.
  • 2+ years of professional experience in machine learning, applied AI, data science, or a closely related field.
  • Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow).
  • Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation.
  • Strong understanding of model evaluation metrics, validation methodologies, and experimental design.
  • Experience with one or more of the following areas: tabular machine learning, natural language processing, computer vision, recommendation systems, ranking systems, time-series forecasting.
  • Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs.

Preferred

  • PhD from a leading research university.
  • Experience at leading technology companies, AI labs, research institutions, or high-growth startups.
  • Participation in competitive machine learning or data science competitions.
  • Experience optimizing models against performance-based evaluation metrics.
  • Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning.
  • Publications, patents, or significant open-source contributions in machine learning or AI.
  • Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners.

Application Process (Takes 20–30 mins to complete)

  • Upload resume
  • AI interview based on your resume
  • Submit form

Resources & Support

  • For details about the interview process and platform information, please check: https://talent.docs.mercor.com/welcome
  • For any help or support, reach out to: support@mercor.com
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FocusMachine Learning EngineeringRole area
Seniority signalSeniorCandidate level
StackPythonPrimary skills
Location1 accepted countryEligibility

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