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.
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