Amazon Web Services (AWS)
Delivery Consultant- GenAI/ML & Data Science, AWS, Industries
Amazon Web Services (AWS), Seattle, Washington, us, 98127
Overview
Delivery Consultant- GenAI/ML & Data Science, AWS, Industries – AWS Professional Services (ProServe) team. In this role, you will work closely with customers to design, implement, and manage AWS solutions that meet technical requirements and business objectives, driving customer success through their cloud journey with technical expertise and best practices throughout the project lifecycle. Responsibilities
Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies Acting as a trusted advisor to customers on industry trends and emerging technologies Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts Qualifications
5+ years of cloud based solution (AWS or equivalent), system, network and operating system experience 5+ years of experience hosting and deploying GenAI/ML solutions (e.g., for data pre-processing, training, deep learning, fine tuning, and inferences) or/and Data Science Experience 5+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python) Preferred Qualifications
PhD or Masters of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience) Knowledge of AWS platform and tools or equivalent cloud experience. Ideally, the candidate has AWS Experience with a proficiency in a wide range of AWS services (e.g. SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2) AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional, Machine Learning Specialty) preferred Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training Experience with coding, automation and scripting (e.g., Terraform, Python) Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Compensation ranges and posting details: The base pay ranges listed reflect different geographic markets and may vary based on job-related knowledge, skills, and experience. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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Delivery Consultant- GenAI/ML & Data Science, AWS, Industries – AWS Professional Services (ProServe) team. In this role, you will work closely with customers to design, implement, and manage AWS solutions that meet technical requirements and business objectives, driving customer success through their cloud journey with technical expertise and best practices throughout the project lifecycle. Responsibilities
Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies Acting as a trusted advisor to customers on industry trends and emerging technologies Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts Qualifications
5+ years of cloud based solution (AWS or equivalent), system, network and operating system experience 5+ years of experience hosting and deploying GenAI/ML solutions (e.g., for data pre-processing, training, deep learning, fine tuning, and inferences) or/and Data Science Experience 5+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python) Preferred Qualifications
PhD or Masters of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience) Knowledge of AWS platform and tools or equivalent cloud experience. Ideally, the candidate has AWS Experience with a proficiency in a wide range of AWS services (e.g. SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2) AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional, Machine Learning Specialty) preferred Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training Experience with coding, automation and scripting (e.g., Terraform, Python) Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. Compensation ranges and posting details: The base pay ranges listed reflect different geographic markets and may vary based on job-related knowledge, skills, and experience. This position will remain posted until filled. Applicants should apply via our internal or external career site.
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