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- Tasks: Collaborate with teams to develop cutting-edge generative AI algorithms and solutions.
- Company: Join AWS, a leader in cloud computing, driving innovation in generative AI.
- Benefits: Enjoy a dynamic work environment with opportunities for growth and collaboration.
- Why this job: Be part of transformative projects that leverage generative AI to solve real-world challenges.
- Qualifications: Bachelor's degree in computer science; experience in software development and machine learning required.
- Other info: Diversity and inclusion are core values at Amazon; we welcome applicants from all backgrounds.
The predicted salary is between 43200 - 72000 £ per year.
Senior ML Engineer, AWS Generative AI Innovation Center
Job ID: 2817053 | AWS EMEA SARL (UK Branch)
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 an ML Engineer, 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 job 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 the implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customers on adoption patterns and 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.
About the team
Generative AI Innovation Center is a program that pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques to:
– Imagine new applications of generative AI to address your needs.
– Identify new use cases based on business value.
– Integrate Generative AI into your existing applications and workflows.
BASIC QUALIFICATIONS
- Bachelor’s degree in computer science or equivalent.
- Experience in professional, non-internship software development.
- Experience coding in Python, R, Matlab, Java or other modern programming languages.
- Several years of relevant experience in developing and deploying large scale machine learning or deep learning models and/or systems into production, including batch and real-time data processing, model containerization, CI/CD pipelines, API development, model training and productionizing ML models.
- Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
PREFERRED QUALIFICATIONS
- Masters or PhD degree in computer science, or related technical, math, or scientific field.
- Proven knowledge of deep learning and experience using Python and frameworks such as Pytorch, TensorFlow.
- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models, experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2, hands-on experience of building ML solutions on AWS.
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts.
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Senior ML Engineer, AWS Generative AI Innovation Center employer: Amazon
Contact Detail:
Amazon Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior ML Engineer, AWS Generative AI Innovation Center
✨Tip Number 1
Familiarize yourself with the latest advancements in generative AI and machine 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 services relevant to the role, such as SageMaker or EC2. Consider building a small project that utilizes these services to demonstrate your practical skills and understanding of the AWS ecosystem.
✨Tip Number 4
Prepare to discuss real-world applications of generative AI during your interview. Think of specific examples where you've successfully implemented ML solutions or how you would approach solving complex problems using generative AI.
We think you need these skills to ace Senior ML Engineer, AWS Generative AI Innovation Center
Some tips for your application 🫡
Understand the Role: Make sure to thoroughly read the job description for the Senior ML Engineer position. Understand the key responsibilities and required qualifications, especially focusing on generative AI and machine learning techniques.
Highlight Relevant Experience: In your application, emphasize your experience with large-scale machine learning models, programming languages like Python or Java, and any hands-on work with AWS services. Tailor your CV to showcase projects that align with the role's requirements.
Showcase Communication Skills: Since strong communication skills are essential for this role, include examples in your cover letter where you successfully conveyed complex technical concepts to non-experts. This will demonstrate your ability to interact with customers effectively.
Prepare a Strong Cover Letter: Craft a compelling cover letter that not only outlines your qualifications but also expresses your passion for generative AI and how you can contribute to the AWS Generative AI Innovation Center. Make it personal and engaging.
How to prepare for a job interview at Amazon
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like PyTorch and TensorFlow. Highlight specific projects where you've implemented generative AI solutions, detailing the challenges you faced and how you overcame them.
✨Understand Customer Engagement
Since the role involves direct interaction with customers, demonstrate your understanding of customer needs and how generative AI can address real-world challenges. Prepare examples of how you've successfully collaborated with clients in previous roles.
✨Communicate Complex Concepts Clearly
You will need to convey rigorous mathematical concepts to non-experts. Practice explaining complex ideas in simple terms, perhaps by using analogies or visual aids, to show that you can bridge the gap between technical and non-technical stakeholders.
✨Familiarize Yourself with AWS Services
Since the position requires knowledge of AWS services, review key services like SageMaker, EMR, and S3. Be ready to discuss how you've utilized these tools in past projects and how they can be leveraged for generative AI applications.
