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Delivery Consultant - Machine Learning (GenAI), ProServe SDT North

Amazon
London
1 month ago
Applications closed

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Delivery Consultant - Machine Learning (GenAI), ProServe SDT North

Job ID: 2944968 | Amazon Web Services EMEA SARL, Dutch Branch

AWS Professional Services is a unique organization. Our customers are most-advanced companies in the world. We build for them world-class, cloud-native IT solutions to solve real business problems and we help them get business outcomes with AWS. Our projects are often unique, one-of-a-kind endeavors that no one ever has done before.

At Amazon Web Services (AWS), we are helping large enterprises build AI solutions on the AWS Cloud. We are applying predictive technology to large volumes of data and against a wide spectrum of problems. AWS Professional Services works together with AWS customers to address their business needs using AI solutions.

As a Delivery Consultant - ML, you will innovate, (re)design and build cloud-native, business-critical AI solutions with our customers. You will take advantage of the global scale, elasticity, automation and high-availability features of the AWS platform. You will build customer solutions with Amazon SageMaker, Amazon Bedrock, Amazon Elastic Compute (EC2), Amazon Data Pipeline, Amazon S3, Glue, Amazon DynamoDB, Amazon Relational Database Service (RDS), Amazon Elastic Map Reduce (EMR), Amazon Kinesis, AWS Lake Formation and other AWS services.

You will collaborate across the whole AWS organization, with other consultants, customer teams and partners on proof-of-concepts, workshops and complex implementation projects. You will innovate and experiment to help Customers achieve their business outcomes and deliver production-ready solutions at global scale. You will lead projects independently but also work as a member of a larger team. Your role will be key to earning customer trust.

This is a customer-facing role. When appropriate and safe, you will be required to visit our office and to travel to client locations to deliver professional services when needed.

You will:

  1. Invent and build AI solutions that solve complex problems, scale globally, guarantee performance, and enable breakthrough innovations.
  2. Use AWS AI/ML services (e.g., Amazon Bedrock), ML platforms (SageMaker), and frameworks (e.g., MXNet, PyTorch, SparkML, scikit-learn) to help our customers build AI/ML solutions.
  3. Work with customers and partners, guiding them through planning, prioritization and delivery of complex transformation initiatives, while collaborating with relevant AWS Sales and Service Teams.
  4. Assist customers by being able to deliver AI/data projects from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organization.
  5. Work with our other Professional Services consultants (GenAI, Big Data, IoT, HPC) to analyze, extract, normalize, and label relevant data, and with our Professional Services engineers to operationalize customers’ models after they are prototyped.
  6. Help customers define their business outcomes and guide their technical architecture and investments.
  7. Create and apply frameworks, methods, best practices and artifacts that will guide our Customers; publish and present them in large forums and across various media platforms.
  8. Contribute to enhancing and improving AWS services.

Our team in AWS Professional Services provides you excellent opportunities to:

  1. Build enterprise-scale AI solutions hands-on on AWS.
  2. Resolve technical challenges in AI, big data, IoT, and more.
  3. Overcome business challenges in different industries.
  4. Develop your leadership skills in Customer engagements.
  5. Influence AWS adoption in our regional market.

Come and Build with us!

BASIC QUALIFICATIONS

- 3+ years experience in the industry as a ML practitioner with hands-on and implementation of ML systems; building, validating and deploying GenAI models.

- 7+ years of professional experience in a business environment; experience of IT platform implementation in a highly technical or analytical role.

- 3+ years experience of handling large datasets and strong software development skills with proficiency in one or more programming languages including Python and one additional language e.g., Java, C#.

- Strong understanding of DevOps practices with practical hands-on application and strong interest in AI/ML solutions. Strong verbal and written communications skills and ability to lead effectively across organizations.

PREFERRED QUALIFICATIONS

- 3+ years Technical experience preferred, knowledge of AI/ML Technology stack of AWS and Generative AI trends, patterns, anti-patterns.

- 3+ years Application Development experience required with serverless technologies and experience training distributed ML models on CPU and GPU hardware.

- Serving ML models through real-time APIs and experience with deploying production-grade machine learning solutions on public cloud platforms.

- Knowledge of vertical use cases for large language models in industries like finance, healthcare, manufacturing etc.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

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.


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