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- Tasks: Join a dynamic team to develop innovative generative AI solutions for real-world challenges.
- Company: AWS is a leading cloud platform, pioneering in technology and innovation.
- Benefits: Enjoy flexible work-life balance, mentorship opportunities, and a culture of inclusion.
- Why this job: Be part of groundbreaking projects that transform businesses and make a social impact.
- Qualifications: Bachelor's degree in computer science or equivalent; coding experience in Python or similar languages required.
- Other info: Diverse experiences are valued; all backgrounds encouraged to apply.
The predicted salary is between 43200 - 72000 £ 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 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 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: The 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.
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.
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.
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.
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.
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:- 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.
- 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 (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer, AWS Generative AI Innovation Center (Basé à London)
✨Tip Number 1
Familiarise yourself with the latest trends in generative AI and machine learning. Being able to discuss recent advancements or case studies during your interactions can demonstrate your passion and knowledge, making you a standout candidate.
✨Tip Number 2
Network with professionals in the field of machine learning and generative AI. Attend relevant meetups, webinars, or conferences to connect with industry experts and gain insights that could be beneficial during interviews.
✨Tip Number 3
Prepare to showcase your problem-solving skills through practical examples. Be ready to discuss specific projects where you've successfully implemented machine learning solutions, particularly those that align with AWS services.
✨Tip Number 4
Understand AWS's culture and values, especially their focus on diversity and inclusion. Be prepared to share how your unique experiences can contribute to their team dynamics and overall mission.
We think you need these skills to ace Machine Learning Engineer, AWS Generative AI Innovation Center (Basé à London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, particularly with generative AI. Include specific projects or roles where you've used Python, R, or other programming languages mentioned in the job description.
Craft a Compelling Cover Letter: In your cover letter, express your passion for generative AI and how your background aligns with the role. Mention any direct experience with AWS services and how you can contribute to the team’s goals.
Showcase Your Projects: If you have worked on any significant machine learning projects, especially those involving generative AI, be sure to include them. Provide links to your GitHub or portfolio to demonstrate your coding skills and project outcomes.
Highlight Communication Skills: Since the role involves interacting with customers and conveying complex concepts, emphasise your communication skills. Provide examples of how you've successfully explained technical topics to non-experts in previous roles.
How to prepare for a job interview at Golden Bees
✨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 and demonstrate your strong communication skills.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Prepare to discuss how you would approach real-world challenges using generative AI, including how you would gather requirements from customers and implement solutions.
