Machine Learning Engineer

Egypt - Cairo

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Rackspace

As a cloud computing services pioneer, we deliver proven multicloud solutions across your apps, data, and security. Maximize the benefits of modern cloud.

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As a full spectrum AWS integrator, we assist hundreds of companies to realize the value, efficiency, and productivity of the cloud. We take customers on their journey to enable, operate, and innovate using cloud technologies – from migration strategy to operational excellence and immersive transformation.
If you like a challenge, you’ll love it here, because we’re solving complex business problems every day, building and promoting great technology solutions that impact our customers’ success. The best part is, we’re committed to you and your growth, both professionally and personally.

Overview

  • As a Machine Learning Engineer, you will deliver ML models and pipelines that solve real-world business problems, while leveraging ML Ops best practices,
  • to ensure successful deployment of ML models and application codeYou will leverage cloud-based architectures and technologies to deliver optimized ML models at scaleYou will use programming languages like Python and work with popular ML frameworks like Scikit Learn, Tensorflow etc..

Responsibilities:

  • Work on full stack technology, from ML and data to production ready models
  • Demonstrable experience in all aspects of the ML lifecycle (processing, training, evaluating, deploying, serving, monitoring)
  • Experienced with Python and modern ML frameworks such as SKLearn, PyTorch or TensorFlow
  • Collaborate with a cross functional agile team spanning design, data science, product management, and engineering to build new technologies and features.
  • Experience in developing scalable data driven solutions while working closely with infrastructure teams.
  • Experience in dealing with databases and building ETL pipelines
  • Atleast one public Cloud knowledge preferred( AWS/Azure/GCP)
  • Strong software development experience with Python or other programming language
  • Strong communication and teamwork skills
  • Passionate about techniques and solving challenging problems

Qualifications & Experience:

  • Experience building and deploying ML models in a Cloud Platform (AWS/Azure/GCP)
  • At least 3 years of experience programming with Python, Scala, or Java
  • 2+ years of experience building end to end data pipelines
  • 2+ experience working on large-scale data science/data analytics projects

About Rackspace TechnologyWe are the multicloud solutions experts. We combine our expertise with the world’s leading technologies — across applications, data and security — to deliver end-to-end solutions. We have a proven record of advising customers based on their business challenges, designing solutions that scale, building and managing those solutions, and optimizing returns into the future. Named a best place to work, year after year according to Fortune, Forbes and Glassdoor, we attract and develop world-class talent. Join us on our mission to embrace technology, empower customers and deliver the future.  More on Rackspace TechnologyThough we’re all different, Rackers thrive through our connection to a central goal: to be a valued member of a winning team on an inspiring mission. We bring our whole selves to work every day. And we embrace the notion that unique perspectives fuel innovation and enable us to best serve our customers and communities around the globe. We welcome you to apply today and want you to know that we are committed to offering equal employment opportunity without regard to age, color, disability, gender reassignment or identity or expression, genetic information, marital or civil partner status, pregnancy or maternity status, military or veteran status, nationality, ethnic or national origin, race, religion or belief, sexual orientation, or any legally protected characteristic. If you have a disability or special need that requires accommodation, please let us know.
Job perks/benefits: Career development
Job region(s): Middle East
Job stats:  10  1  0
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