At a Glance
- Tasks: Design and develop cutting-edge generative AI algorithms to solve real-world challenges.
- Company: Join AWS, the leading cloud platform trusted by startups and Global 500 companies.
- Benefits: Enjoy flexible work-life balance, mentorship opportunities, and a culture of inclusion.
- Why this job: Be part of a fast-paced team innovating game-changing AI solutions that delight customers.
- Qualifications: Bachelor's in computer science or related field; experience in deep learning and cloud solutions required.
- Other info: Diverse and inclusive team culture with ongoing learning experiences.
The predicted salary is between 43200 - 72000 £ per year.
Job Description
The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
As a Deep Learning Architect, you’ll partner with technology and business teams to build solutions that surprise and delight our customers. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.
We’re looking for Engineers and Architects capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
Key Responsibilities
- Collaborate with ML scientists and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges.
- Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership.
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and productionization paths for generative AI.
- Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on the AWS platform.
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholders.
- Provide customer and market feedback to Product and Engineering teams to help define product direction.
Minimum Qualifications
- Bachelor’s degree in computer science, engineering, mathematics or equivalent.
- Experience in design, implementation, or consulting in applications and infrastructures.
- Experience architecting or deploying Cloud/Virtualization solutions in enterprise customers.
- Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences).
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field.
Preferred Qualifications
- MSc degree in computer science, engineering, mathematics or equivalent.
- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models.
- Proven knowledge of AWS platform and tools.
- Hands-on experience of building ML solutions on AWS.
- Experience in professional software development.
About the Team
GenAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. As a Data Science Manager in GenAIIC, you’ll partner with technology and business teams to build new generative AI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems.
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.
Equal Opportunity Employer
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.
For individuals with disabilities who would like to request an accommodation, please visit here .
#J-18808-Ljbffr
Deep Learning Architect, AWS Generative AI Innovation Center employer: AWS EMEA SARL (UK Branch)
Contact Detail:
AWS EMEA SARL (UK Branch) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Deep Learning Architect, AWS Generative AI Innovation Center
✨Tip Number 1
Familiarize yourself with the latest advancements in generative AI and deep learning. Being well-versed in current trends and technologies will not only help you during interviews but also demonstrate your passion for the field.
✨Tip Number 2
Engage with the AWS community by participating in forums, webinars, or local meetups focused on generative AI and machine learning. Networking with professionals in the field can provide valuable insights and potentially lead to referrals.
✨Tip Number 3
Showcase your hands-on experience with AWS tools and services by working on personal projects or contributing to open-source initiatives. This practical experience will be crucial in demonstrating your capabilities to potential employers.
✨Tip Number 4
Prepare to discuss real-world applications of generative AI during interviews. Think of specific examples where you've successfully implemented solutions or contributed to projects that utilized deep learning techniques.
We think you need these skills to ace Deep Learning Architect, AWS Generative AI Innovation Center
Some tips for your application 🫡
Tailor Your Resume: Make sure your resume highlights relevant experience in deep learning, generative AI, and cloud solutions. Use specific examples of projects you've worked on that align with the responsibilities mentioned in the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for generative AI and how your background makes you a perfect fit for the role. Mention any direct experience with AWS tools and platforms, and how you can contribute to the team’s goals.
Showcase Your Technical Skills: Include a section in your application that lists your technical skills, particularly those related to deep learning frameworks, AWS services, and any programming languages you are proficient in. This will help demonstrate your qualifications at a glance.
Highlight Collaboration Experience: Since the role involves working closely with ML scientists and engineers, emphasize any past experiences where you collaborated on projects. Discuss how you contributed to team success and what you learned from those interactions.
How to prepare for a job interview at AWS EMEA SARL (UK Branch)
✨Showcase Your Technical Expertise
Be prepared to discuss your experience with deep learning and generative AI. Highlight specific projects where you've designed or implemented ML solutions, especially those involving AWS tools.
✨Understand Customer Engagement
Demonstrate your ability to interact with customers by sharing examples of how you've identified their needs and delivered tailored solutions. This will show that you can bridge the gap between technology and business.
✨Prepare for Problem-Solving Scenarios
Expect to tackle real-world challenges during the interview. Practice articulating your thought process in solving complex problems using generative AI techniques, as this reflects the role's focus on innovation.
✨Emphasize Collaboration Skills
Since the role involves working with cross-functional teams, be ready to discuss your experiences collaborating with ML scientists, engineers, and other stakeholders. Highlight how you contributed to team success and shared knowledge.