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- Tasks: Develop and research machine learning solutions for Amazon's transportation systems.
- Company: Join Amazon, a leader in e-commerce and innovative technology.
- Benefits: Enjoy flexible work options, competitive pay, and a vibrant company culture.
- Why this job: Make a real impact on sustainability and customer experience in a fast-paced environment.
- Qualifications: PhD or Master's in relevant fields; programming skills in Java, C++, or Python required.
- Other info: Diverse and inclusive workplace with opportunities for growth and innovation.
The predicted salary is between 43200 - 72000 £ per year.
Are you interested in building state-of-the-art machine learning systems for the most complex, and fastest growing, transportation network in the world? If so, Amazon has the most exciting, and never-before-seen, challenges at this scale (including those in sustainability, e.g. how to reach net zero carbon by 2040).
Amazon’s transportation systems get millions of packages to customers worldwide faster and cheaper while providing world class customer experience – from online checkout, to shipment planning, fulfillment, and delivery. Our software systems include services that use tens of thousands of signals every second to make business decisions impacting billions of dollars a year, that integrate with a network of small and large carriers worldwide, that manage business rules for millions of unique products, and that improve experience of over hundreds of millions of online shoppers.
EU STEP brings together Supply Chain, Network Design, and Transportation Planning teams to improve end-to-end forecasting, network flow, planning, and execution. It also brings together our teams from across the business focused on our Operational Excellence pillars - Amazon Customer Excellence Systems (ACES), Learning, Quality, Service, Sustainability and Reliability Maintenance Engineering (RME) Field teams. This integration strengthens operations and execution while driving quality improvements and enhanced customer experience across the entire value chain.
As part of this team you will focus on the development and research of machine learning solutions and algorithms for core planning systems, as well as for other applications within Amazon Transportation Services, and impact the future of the Amazon delivery network. Current research and areas of work within our team include machine learning forecasting, planning systems and robust decision making on large networks, as well as uncertainty quantification, generative models on graphs and ml explainability, among others.
We are looking for an Applied Scientist with a strong academic background in the areas of machine learning, time series forecasting, and/or optimization.
At Amazon, we strive to continue being the most customer-centric company on earth. To stay there and continue improving, we need exceptionally talented, bright, and driven people. If you’d like to help us build the place to find and buy anything online, and deliver in the most efficient and greenest way possible, this is your chance to make history.
About the team: The EU ATS Science and Technology (SnT) team owns scalable algorithms, models and systems that improve customer experience in middle-mile. We work backwards from Amazon's customers aiming to make transportation faster, cheaper, safer, more reliable and ecologically sustainable.
- BASIC QUALIFICATIONS
- PhD, or a Master's degree and experience in CS, CE, ML or related field
- Experience in building models for business application
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
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.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information.
Applied Scientist, ATS Machine Learning & Engineering (ML&E) (Basé à London) employer: Golden Bees
Contact Detail:
Golden Bees Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Applied Scientist, ATS Machine Learning & Engineering (ML&E) (Basé à London)
✨Tip Number 1
Familiarise yourself with Amazon's machine learning frameworks and tools. Understanding their specific technologies, such as SageMaker, can give you an edge in discussions during interviews.
✨Tip Number 2
Engage with the machine learning community by attending relevant conferences or webinars. Networking with professionals in the field can provide insights into current trends and challenges that Amazon is facing.
✨Tip Number 3
Prepare to discuss your previous projects in detail, especially those involving machine learning applications. Be ready to explain your thought process, the challenges you faced, and how you overcame them.
✨Tip Number 4
Stay updated on Amazon's sustainability initiatives, particularly in transportation. Showing your knowledge and passion for their goals, like achieving net zero carbon by 2040, can demonstrate your alignment with their values.
We think you need these skills to ace Applied Scientist, ATS Machine Learning & Engineering (ML&E) (Basé à London)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your academic background in machine learning, time series forecasting, and optimisation. Include relevant projects or experiences that demonstrate your skills in building models for business applications.
Craft a Strong Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with Amazon's mission to improve customer experience. Mention specific areas of research you are interested in, such as generative models or uncertainty quantification.
Showcase Publications and Patents: If you have any publications or patents, make sure to include them in your application. Highlighting your contributions to top-tier peer-reviewed conferences or journals can set you apart from other candidates.
Highlight Technical Skills: Clearly list your programming skills, especially in Java, C++, and Python. If you have experience with Unix/Linux or professional software development, be sure to mention that as well, as it is preferred by the company.
How to prepare for a job interview at Golden Bees
✨Showcase Your Technical Skills
Be prepared to discuss your experience with machine learning, time series forecasting, and optimisation. Bring examples of models you've built or worked on, and be ready to explain the algorithms and techniques you used.
✨Demonstrate Problem-Solving Abilities
Expect to face technical challenges during the interview. Practice solving problems related to algorithms, data structures, and numerical optimisation. Think aloud as you work through these problems to showcase your thought process.
✨Familiarise Yourself with Amazon's Culture
Understand Amazon's leadership principles and how they apply to the role. Be ready to discuss how your values align with theirs, particularly in terms of customer obsession and innovation.
✨Prepare Questions for Your Interviewers
Have insightful questions ready about the team, projects, and future directions of Amazon's transportation systems. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
