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Machine Learning Engineer

micro1

3.7
99 reviews
micro1
Job Type   /   Job Level
Full-time   /   Junior Executive
Job Location
NAMER
Salary Range
USD 10,000 - USD 16,000 (Monthly)
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Job Title: Machine Learning Engineer


Job Type: Contractor


Location: Remote


Job Summary:

In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters.


Key Responsibilities:

  • Develop, train, and deploy machine learning models using TensorFlow and Scikit-Learn to address real-world business problems.
  • Conduct comprehensive data preprocessing, including data cleaning, transformation, and feature engineering to ensure high-quality inputs for model development.
  • Collaborate with data scientists, data engineers, and business analysts to understand requirements and translate them into scalable ML solutions.
  • Continuously monitor, evaluate, and refine model performance to ensure accuracy, efficiency, and reliability in production environments.
  • Document model development processes and proactively communicate technical concepts and results with both technical and non-technical team members.
  • Stay abreast of the latest research and advancements in machine learning and apply innovative techniques to enhance project outcomes.
  • Contribute to a culture of knowledge sharing, mentorship, and continuous improvement within the customer's team.


Required Skills and Qualifications:

  • Expert-level proficiency in TensorFlow and Scikit-Learn for end-to-end model development and deployment.
  • Strong background in data preprocessing, including handling missing values, outlier detection, and feature selection.
  • Excellent written and verbal communication skills, with the ability to convey complex technical information clearly.
  • Demonstrated experience in designing and implementing production-ready machine learning systems.
  • Solid understanding of algorithm selection, model evaluation metrics, and performance tuning.
  • Ability to work independently and remotely, delivering results in a fast-paced, deadline-driven environment.
  • Detail-oriented with exceptional problem-solving and analytical skills.
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