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- Tasks: Collaborate with teams to develop innovative generative AI solutions for real-world challenges.
- Company: Join AWS, the leading cloud platform, known for its innovation and diverse culture.
- Benefits: Enjoy flexible work-life balance, mentorship opportunities, and a culture of inclusion.
- Why this job: Be part of a dynamic team that shapes the future of AI technology and customer experiences.
- Qualifications: Bachelor's degree in computer science or equivalent; experience in software development and machine learning required.
- Other info: Diverse backgrounds are encouraged; apply even if you don't meet all qualifications.
The predicted salary is between 36000 - 60000 £ per year.
The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realise 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, evangelise, 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 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 paths for generative AI.
- Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on 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.
Diverse Experiences: 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.
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 language.
- 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 productionising 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.
Machine Learning Engineer, AWS Generative AI Innovation Center employer: Amazon Web Services (AWS)
Contact Detail:
Amazon Web Services (AWS) Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, AWS Generative AI Innovation Center
✨Tip Number 1
Familiarise yourself with AWS services, especially those mentioned in the job description like SageMaker and EC2. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your commitment to the role.
✨Tip Number 2
Engage with the generative AI community online. Participate in forums, attend webinars, or join relevant groups on platforms like LinkedIn. This will help you stay updated on trends and best practices, which can be valuable during interviews.
✨Tip Number 3
Prepare to discuss real-world applications of generative AI. Think of specific examples where you've used or could use generative AI to solve problems. This will show your practical understanding and ability to apply your knowledge effectively.
✨Tip Number 4
Network with current or former employees of AWS, particularly those in the Generative AI Innovation Center. They can provide insights into the company culture and expectations, which can be incredibly helpful for tailoring your approach.
We think you need these skills to ace Machine Learning Engineer, AWS Generative AI Innovation Center
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with generative AI and AWS services. Use specific examples of projects you've worked on that align with the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for generative AI and how your skills can contribute to AWS's mission. Mention any direct experience with AWS tools and frameworks, and how you can help customers implement innovative solutions.
Showcase Technical Skills: Clearly outline your technical skills in programming languages like Python or R, and your experience with deep learning frameworks such as TensorFlow or PyTorch. Provide examples of how you've applied these skills in real-world scenarios.
Highlight Collaboration Experience: Since the role involves working with cross-functional teams, emphasise your experience collaborating with others. Share specific instances where you successfully partnered with different stakeholders to achieve project goals.
How to prepare for a job interview at Amazon Web Services (AWS)
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning frameworks like TensorFlow or PyTorch. Bring examples of projects where you've implemented generative AI solutions, and be ready to explain the algorithms you used and the challenges you faced.
✨Understand AWS Services
Familiarise yourself with AWS services relevant to machine learning, such as SageMaker and EC2. Demonstrating knowledge of how these services can be leveraged for generative AI will show your potential employer that you're ready to hit the ground running.
✨Communicate Clearly
Since you'll be interacting with customers and stakeholders, practice explaining complex technical concepts in simple terms. This will help you convey your ideas effectively during the interview and demonstrate your communication skills.
✨Prepare for Problem-Solving Questions
Expect to face scenario-based questions that assess your problem-solving abilities. Think about real-world challenges you've encountered in previous roles and how you approached them, especially in relation to generative AI and machine learning.
