Sr Machine Learning Engineer (GCP)
United States - Remote
Rackspace
As a cloud computing services pioneer, we deliver proven multicloud solutions across your apps, data, and security. Maximize the benefits of modern cloud.What you will be doing:
- Develop and implement automation and DevOps methodologies, including CI/CD, Infrastructure as Code (IaC), and containerization, to establish a scalable Machine Learning infrastructure.
- Design and execute automation strategies, encompassing DevOps pipelines, scripting, and Terraform-based Infrastructure as Code.
- Engage actively in client sessions to understand and address their needs.
- Prepare and maintain detailed technical documentation.
Requirements:
- Experienced with machine learning frameworks (TensorFlow, PyTorch) and libraries (e.g., scikit-learn).
- Expertise in public cloud services, particularly in GCP.
- Experienced working with vertexAI, Automl and other GCP AI and Machine learning services.
- Experience with GCP managed services and understanding of cloud-based messaging/stream processing systems are critical.
- Experienced in Infrastructure and Applied DevOps principles in daily work. Utilize tools for continuous integration and continuous deployment (CI/CD), and Infrastructure as Code (IaC) like Terraform to automate and improve development and release processes.
- Has knowledge in containerization technologies such as Docker and Kubernetes to enhance the scalability and efficiency of applications.
- Worked effectively in a remote setting, maintaining strong written and verbal communication skills. Collaborate with team members and stakeholders, ensuring clear understanding of technical requirements and project goals.
- Proven experience in engineering machine learning systems at scale.
- Strong programming abilities in Java and Python.
- Hands-on experience in public cloud platforms, particularly GCP. Additional experience with other cloud technologies is advantageous.
Must Have:
- Google Google Cloud Professional level certification, Devops and machine learning.
- 4+ years of experience in customer-facing software/technology or consulting
- 4+ years of experience with “on-premises to cloud” migrations or IT transformations
- 4+ years of experience building, and operating solutions built on GCP (ideally) or AWS/Azure
- Technical degree: Computer Science, software engineering or related
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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: AWS Azure CI/CD Computer Science Consulting DevOps Docker Engineering GCP Google Cloud Java Kubernetes Machine Learning ML infrastructure Pipelines Python PyTorch Scikit-learn Security TensorFlow Terraform
Perks/benefits: Career development
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