Unknown Company

Machine Learning Engineer (Malayalee preferred) in Akron, USA

akron, oh • Posted 2 weeks ago
Onsite Full Time Electrical & Energy Engineering

A fast-growing tech company in Akron is seeking a highly motivated and skilled Machine Learning Engineer to join our team. As a Machine Learning Engineer you will be responsible for developing and implementing machine learning algorithms and models to improve our products and services. This is a full-time position with a salary of 900$ per month.

Responsibilities

  • Conduct research and develop machine learning algorithms and models
  • Collect organize and analyze large datasets to identify trends and patterns
  • Collaborate with cross-functional teams to understand business needs and develop solutions
  • Develop prototypes and proof-of-concepts to demonstrate the effectiveness of machine learning solutions
  • Monitor model performance and make necessary improvements
  • Stay updated on the latest developments in machine learning techniques and tools

Requirements

  • Bachelors or Masters degree in Computer Science Data Science or related field
  • Strong programming skills in languages such as Python Java or C++
  • Experience with machine learning frameworks such as TensorFlow or PyTorch
  • Knowledge of data mining statistical analysis and predictive modeling techniques
  • Excellent communication skills and ability to work in a collaborative team environment

Preferred

  • Malayalee nationality preferred
  • Fluent in English reading writing speaking
  • Previous experience working with large datasets
  • Familiarity with cloud computing platforms such as AWS or Azure

We offer competitive salary packages along with free visa sponsorship and travel ticket for eligible candidates.

This is an excellent opportunity for freshers without any prior experience to kickstart their career in the exciting field of machine learning.

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Machine Learning Engineer (Malayalee preferred) in Akron, USA in akron at Unknown Company

This position is listed as full time and onsite.

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