At a Glance
- Tasks: Help customers design AI/ML solutions using AWS tools and techniques.
- Company: Join Amazon, a leader in AI innovation with over 20 years of experience.
- Benefits: Enjoy flexible work-life balance, mentorship opportunities, and a culture of inclusion.
- Why this job: Be at the forefront of AI technology while making a global impact.
- Qualifications: 8+ years in tech, with strong AI/ML expertise and a math background preferred.
- Other info: Travel up to 50% across EMEA; diverse experiences encouraged.
The predicted salary is between 72000 - 108000 £ per year.
Sr Worldwide Specialist Solutions Architect – GenAI, Amazon SageMaker Job ID: 2858333 | AWS EMEA SARL (UK Branch) Are you passionate about Artificial Intelligence, Machine Learning and Deep Learning? Are you passionate about helping customers build solutions leveraging the state-of-the-art AI/ML/DL tools on Amazon Web Service (AWS)? Come join us! At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning (ML), as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition deep learning; as is Prime Air, and the computer vision technology in our new retail experience, Amazon Go. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage. Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Lex, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with a simple API call. AWS is looking for a GenAI/ML Solutions Architect (GenAI/ML SA), who will be the Subject Matter Expert (SME) for helping customers worldwide design solutions that leverage our ML services. This role will specifically specialize in using state-of-the-art techniques to pre-train and fine-tune foundation models. As part of the team, you will work closely with customers to enable large-scale use cases, design ML pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage AI/ML on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward. You must have deep technical experience working with technologies related to artificial intelligence, specifically in advanced generative AI technologies. A strong mathematics and statistics background is preferred in addition to experience fine-tuning foundation models. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process. If you are a qualified and accepted candidate, you may work out of London. Travel up to 50% across the EMEA may be possible. Key job responsibilities Thought Leadership – Promote AWS GenAI/ML services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. Partner with SAs, Sales, Business Development and the AI/ML Service teams to accelerate customer adoption and revenue attainment worldwide for Amazon SageMaker. Act as a technical liaison between customers and the AWS SageMaker services teams to provide customer driven product improvement feedback. Develop and support an AWS internal community of ML related subject matter experts worldwide. About the team AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud. BASIC QUALIFICATIONS – 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience – 3+ years of design, implementation, or consulting in applications and infrastructures experience – 10+ years of IT development or implementation/consulting in the software or Internet industries experience PREFERRED QUALIFICATIONS – 5+ years of infrastructure architecture, database architecture and networking experience – Experience working with end user or developer communities #J-18808-Ljbffr
Sr Worldwide Specialist Solutions Architect - GenAI, Amazon SageMaker employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Sr Worldwide Specialist Solutions Architect - GenAI, Amazon SageMaker
✨Tip Number 1
Familiarize yourself with AWS services, especially Amazon SageMaker and its capabilities. Understanding how to leverage these tools will not only help you in interviews but also demonstrate your genuine interest in the role.
✨Tip Number 2
Engage with the AI/ML community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into industry trends and may even lead to valuable connections at AWS.
✨Tip Number 3
Showcase your thought leadership by writing articles or blogs about generative AI and machine learning. This will not only enhance your visibility but also align with AWS's emphasis on sharing best practices.
✨Tip Number 4
Prepare to discuss specific use cases where you've successfully implemented AI/ML solutions. Being able to articulate your hands-on experience will set you apart as a candidate who can drive customer adoption effectively.
We think you need these skills to ace Sr Worldwide Specialist Solutions Architect - GenAI, Amazon SageMaker
Some tips for your application 🫡
Highlight Relevant Experience: Make sure to emphasize your experience in artificial intelligence, machine learning, and deep learning. Detail specific projects or roles where you utilized AWS services, particularly Amazon SageMaker.
Showcase Thought Leadership: Demonstrate your ability to promote AI/ML services by mentioning any blogs, white papers, or presentations you've created. This will show your commitment to sharing knowledge and best practices in the field.
Tailor Your Application: Customize your CV and cover letter to reflect the key responsibilities and qualifications listed in the job description. Use keywords from the posting to ensure your application resonates with the hiring team.
Express Passion for AI/ML: Convey your enthusiasm for artificial intelligence and machine learning in your application. Share why you are excited about the opportunity to work with AWS and how you can contribute to their mission.
How to prepare for a job interview at Amazon
✨Show Your Passion for AI/ML
Make sure to express your enthusiasm for artificial intelligence, machine learning, and deep learning during the interview. Share specific examples of projects or experiences where you've leveraged these technologies, especially in relation to AWS services.
✨Demonstrate Technical Expertise
Prepare to discuss your technical background in detail, particularly your experience with generative AI technologies and fine-tuning foundation models. Be ready to answer technical questions and provide insights into how you can help customers design effective ML solutions.
✨Highlight Collaboration Skills
Since this role involves working closely with various teams, emphasize your ability to collaborate effectively. Share examples of how you've partnered with sales, business development, or technical teams to drive customer adoption and success.
✨Prepare Thought Leadership Examples
Be ready to discuss any thought leadership initiatives you've been involved in, such as writing blogs, white papers, or presenting at conferences. This will demonstrate your commitment to sharing knowledge and best practices in the AI/ML space.