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Deloitte Sr. AWS-ML-Sagemaker Engineer in Tempe, Arizona

Senior AWS-ML-Sagemaker Engineer

Are you an experienced, passionate pioneer in technology? A cloud solutions builder who wants to work in a collaborative environment. As an experienced Senior AWS-ML-Sagemaker Engineer

you will have the ability to share new ideas and collaborate on projects as a consultant without the extensive demands of travel. Consider an opportunity with our US Delivery Center - we are breaking the mold of a typical Delivery Center.

Our US Delivery Centers have been growing since 2014 with significant, continued growth on the horizon. Interested? Read more about our opportunity below ...

Work you'll do/Responsibilities.

  • Be well-versed in cloud technologies, specifically AWS services, and have a robust understanding of Machine Learning models, especially in the domain of AWS Sagemaker.

  • Collaborate closely with Cloud Infrastructure Engineers to enhance our AIOps product development for Deloitte Cloud Managed Services.

  • Analyze vast amounts of cloud infrastructure log data to extract meaningful insights.

  • Design, develop, and deploy Machine Learning models on AWS Sagemaker.

  • Enable smart alerting mechanisms to notify stakeholders of potential system threats or outages.

  • Implement anomaly detection models to proactively identify system outages or failures.

  • Build security models to detect potential threats and vulnerabilities within the cloud infrastructure.

  • Optimize models for scalability, efficiency, and real-time performance.

  • Document all processes, models, and procedures to ensure best practices.

  • Stay up-to-date with the latest industry trends and technologies to ensure our solutions remain cutting-edge.

The Team

Deloitte's Government & Public Services practice-our people, ideas, technology and outcomes-is designed for impact. Our team of over 15,000+ professionals bring fresh perspective to help you anticipate disruption, reimagine the possible, and fulfill your mission promise.

The US Cloud Engineering Offering focuses on enabling our client's end-to-end journey from On-Premise to Cloud, with opportunities in the areas of Cloud Strategy and Op Model Transformation, Cloud Development & Integration, Cloud Migration, and Cloud Infrastructure & Managed Services. Cloud Engineering supports our clients as they improve agility, resilience and identifies opportunities to reduce IT operations spend through automation by enabling Cloud. We accelerate our clients toward a technology-driven future, leveraging vendor solutions, Deloitte-developed software products, tools, and accelerators.

Required Qualifications

  • Bachelor's Degree preferably in Computer Science, Engineering, Management Information Systems or equivalent work experience

  • 5+ years of experience with AWS services, with a focus on Sagemaker.

  • Demonstrated experience working within AWS cloud environments, base understanding of AWS services and able to navigate console as well as utilize AWS command line interface CLI.

  • Experience enhancing Cloud Operations Efficiency through AI/ML-driven Automation.

  • Proven expertise in Machine Learning model development, training, and deployment.

  • Strong understanding of cloud infrastructure and log data analysis.

  • Knowledge of AIOps and its application in cloud managed services.

  • Proficiency in programming languages such as Python, R, or Java.

  • Strong problem-solving skills and analytical mindset.

  • Demonstrate strong communication skills to translate technical software solutions to non-technical clients.

  • Must be in your designated office location 10%-30% of each work week.

  • Ability to travel 10% on average, based on the work you do, the clients you serve and industries/sectors you serve.

  • Must live near the Lake Mary, FL; Gilbert, AZ; or Mechanicsburg, PA areas.

  • Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future.

Preferred Qualifications:

  • AWS Certifications, especially in Machine Learning or Big Data.

  • Experience with other AWS services like Lambda, EC2, RDS, Kinesis, etc.

  • Familiarity with other cloud platforms like Azure or Google Cloud.

  • Prior experience in a product development environment.

    All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability or protected veteran status, or any other legally protected basis, in accordance with applicable law.