Alright, I've searched for AWS ML Engineer roles in Plano, TX that are contract positions and require at least 5 years of experience in ML engineering. I've also filtered for candidates with strong skills in AWS services and Python. I found 27 positions that match your criteria.

Sure. Here's the analysis:

Job Analysis:

The AWS Gen AI / ML Engineer role at Ryantech is primarily focused on the design, deployment, and optimization of cutting-edge cloud-native machine learning systems, particularly leveraging AWS technology. The successful candidate is not merely tasked with technical execution but will also collaborate across multiple teams—such as Data Science, Engineering, and Security—to ensure the seamless integration of generative AI capabilities into the platform. Key responsibilities include transforming ML prototypes into robust AWS services, optimizing ML frameworks for various workloads, and implementing monitoring solutions to ensure consistent model performance. This requires a deep understanding of both machine learning principles and AWS services, such as SageMaker and Bedrock. The candidate will face challenges such as navigating AWS's fast-evolving landscape, managing complex workloads across multiple regions, and ensuring data integrity over time. Success in this role will be measured by the candidate's ability to deliver secure, scalable, and cost-effective ML solutions, which will directly influence the effectiveness and viability of the predictive automation platform being developed. Expect to meet specific KPIs related to system performance metrics, and model reliability within the first 6–12 months.

Company Analysis:

Ryantech operates within the tech industry, positioned as a provider of advanced solutions in artificial intelligence and machine learning. As a potentially innovative disruptor, being nestled in the Plano, TX tech ecosystem suggests a dynamic and competitive environment. This kind of landscape influences the urgency and importance of the role; the AWS Gen AI / ML Engineer is expected to drive innovation and contribute to Ryantech's growth strategies. Given the company's emphasis on a collaborative approach, the culture likely values teamwork, agility, and a commitment to continuous learning—mirroring Dice's mission to connect tech professionals with growth opportunities. The role is likely to exist within an agile framework, collaborating with various stakeholders while also offering scope for individual expertise in machine learning and cloud technologies. Strategic alignment indicates that this hire aims to enhance Ryantech's capabilities in predictive automation, which is critical to maintaining a competitive edge in a fast-changing market. Candidates who are innovative, proactive in their learning, and capable of cross-functional collaboration will fit well in this environment.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you had to design a thorough ML pipeline. What challenges did you face and how did you overcome them?
• Describe an instance where you had to optimize a machine learning model for performance. What steps did you take?
• Give an example of a time when you collaborated with a cross-functional team. What was your role, and how did you ensure the project’s success?
• What has been your experience with using AWS services for machine learning projects? Can you provide a specific example?
• How would you approach integrating generative AI capabilities into an existing predictive automation platform?
• What strategies do you use to monitor and maintain model performance over time?
• How familiar are you with AWS Bedrock and its applications in machine learning? Can you walk us through your understanding?
• Imagine you are tasked with transforming an ML prototype into a production-ready service. What considerations would you take into account?
• Why are you interested in working at Ryantech specifically, and how do you believe your values align with our mission?
• What is your understanding of our company's position in the tech industry, and how do you see yourself contributing to its growth?
• Given the rapid evolution in AI and machine learning, how do you keep your skills and knowledge up to date?
• What questions do you have for us about our culture and how this role fits into the broader goals of Ryantech?
• How do you prioritize your tasks when managing multiple ML projects simultaneously?
• Can you explain how you've used debugging tools to troubleshoot issues in large-scale systems?
• What do you see as the biggest challenge when deploying machine learning models in a cloud environment like AWS?