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senior machine learning engineer

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Machine Learning Engineering, Amazon SageMaker, Amazon Web Services, Python
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Armenia, Georgia, India, Kazakhstan, Kyrgyzstan, Uzbekistan

We are looking for a remote Senior Machine Learning Engineer to join our team and work on an exciting project involving Amazon Web Services. The project requires the development and deployment of Machine Learning (ML) models using various AWS components and tools. As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and implementing ML models, along with managing the entire ML lifecycle. You will also work closely with cross-functional teams and stakeholders to deliver high-quality ML solutions that meet business requirements.

responsibilities
  • Design, develop, and implement ML models using AWS components and tools, such as Amazon SageMaker
  • Manage the entire ML lifecycle, from data preparation to model deployment and monitoring
  • Work with cross-functional teams and stakeholders to understand business requirements and deliver high-quality ML solutions that meet those requirements
  • Develop and maintain ML documentation, such as model design, training, and testing results
  • Keep up-to-date with the latest ML technologies and trends, and apply them to improve existing ML solutions
  • Collaborate with the team members to enhance technical and soft skills
requirements
  • Minimum of 3 years of experience in Machine Learning Engineering
  • Proven experience in designing and deploying ML models using Amazon SageMaker and AWS ecosystem
  • Expertise in Python
  • Proficiency with entire ML lifecycle, from data preparation to model deployment and monitoring
  • Experience in working with cross-functional teams and stakeholders to deliver high-quality ML solutions
  • Strong communication skills, able to convey technical concepts to non-technical stakeholders
  • Fluent in English language, with at least an upper-intermediate level competency for effective communication with the team and stakeholders
nice to have
  • Experience in building model artifacts and deploying them to the AWS ecosystem

benefits for locations

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For you
  • Medical insurance package for you and your family
  • Stable income
  • Paid sick leave days
For your comfortable work
  • 100% remote work forever
  • Free licensed software
  • Possibility to work on your own device (BYOD)
  • Stable workload
  • Relocation opportunities
  • Flexible engagement models
For your growth
  • Free trainings for technical, soft, and leadership skills
  • Access to LinkedIn Learning platform
  • Language courses
  • Access to internal and external e-Libraries
  • Certification opportunities
  • Skill advisory service
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