Machine Learning Systems Engineer

11 hours ago


Bengaluru, Karnataka, India Saarthee Full time
Job Title

Machine Learning Systems Engineer

About Our Team

Saarthee's mission is to push the boundaries of machine learning engineering and make it more accessible to everyone.

Estimated Salary Range

$155,000 - $205,000 per year

Job Overview

We're looking for an experienced machine learning systems engineer to develop and implement large-scale machine learning systems. The ideal candidate will have expertise in designing, coding, training, documenting, deploying, and evaluating machine learning systems.

Main Responsibilities:
  • Design, code, and train machine learning models for various applications, including predictive safety, content personalization, search, virtual assistant, time series forecasting, and clustering.
  • Implement and optimize machine learning models using state-of-the-art technologies, such as deep learning and transfer learning.
  • Work collaboratively with cross-functional teams to understand business requirements and translate them into analytical solutions.
  • Analyze large datasets to uncover patterns, trends, and valuable insights.
  • Deploy machine learning models into production environments using cloud services and implement scalable and efficient solutions for real-time and batch predictions.
Requirements:
  • Bachelor's degree in computer science, Engineering, Statistics, or a related field.
  • 5+ years of experience in machine learning engineering, with expertise in deep learning, transfer learning, and model optimization.
  • Proficiency in Python programming language and experience with popular libraries like PyTorch and TensorFlow.
  • Strong understanding of machine learning algorithms, including supervised and unsupervised learning.
  • Excellent communication and collaboration skills.
Why Work with Us?
  • Above industry remuneration: $155,000 - $205,000 per year.
  • Opportunities for growth and professional development.
  • Collaborative and dynamic work environment.
  • Chance to work on challenging projects and make a meaningful impact.
  • Competitive benefits package.


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