Amazon’s Intelligent Cloud Control Group in Berlin is looking for an Applied Science Manager to lead the research and development of large-scale machine learning implementations that will revolutionize the way Amazon operates the tens of thousands of software services and subcomponents across their retail businesses. With an ever-growing number of fleets, developers, customers, products, marketplaces, sellers, and businesses, the Amazon service graph is one of the largest and most complex tech ecosystems in the world. They are building an Intelligent Cloud Control system that enables Amazon businesses (Retail, Amazon Video, Kindle, and more) to accelerate innovation in the cloud.
As an Applied Science Manager in the Intelligent Cloud Control team, you’ll leverage your own skills and those of your team of machine learning engineers, data scientists, and applied scientists to develop and evaluate machine learning models using extremely large datasets such as the orders, website traffic, telemetry, and logs from every host at Amazon. Their datasets extend into the multi-exabyte range, and Amazons’ science products are of critical importance to the retail businesses of Amazon. You will own researching, developing, prioritizing, and releasing both prototypes and reliable automated production workflow for the model. You will collaborate with other managers and leaders to improve the Amazon retail customer experience.
Their responsibility is to maximize the availability and contribute to the better efficiency of Amazon’s retail experience, so Amazons’ opportunities are endless. From natural language processing and information extraction of operational issues to unsupervised multi-variate anomaly detection to discover nodes of linked sub-system behaviour, the insights and opportunities to discover and remediate customer-impacting issues are profound and their solutions worthy of publication.
Amazon is looking for engineers capable of using machine learning and other techniques to design, evaluate, and implement state-of-the-art solutions for never-before-solved problems.
- Health: Medical plan options give you the flexibility to select the right health care coverage for you and eligible family members. Choose from several plans, including a Health Savings Account (with employee and employer contributions), and multiple network providers for the best care in your area. You can also enrol in Dental and Vision plans as well as a Flexible Spending Accounts for health and dependent care.
- Financial Security:
- Amazon’s 401(k) plan provides you with an opportunity to defer compensation for your long-term savings and includes a company match. The plan offers a variety of investment options to help you reach your financial goals.
- Company-paid basic Life and Accidental Death & Dismemberment Insurance with the option to enrol in additional coverage for you and your dependents.
- Company-paid Short-Term and Long-Term Disability.
- Restricted Stock Units (RSUs)
- At Amazon, most employees have the ability to become owners of the company through the granting and vesting of Restricted Stock Units. Amazon is continually evaluating new ways to provide other types of ownership opportunities for all employees.
- A network of Support:
- Amazon cares about your health and well-being, both on and off the job. The following benefits are available at no cost to help make life a little bit easier.
- Amazon’s free Employee Assistance Program provides confidential 24/7 support, resources and referrals for every aspect of work and personal life.
- Online resources for parents whose children struggle with developmental disabilities, as well as help finding a child and elder care referrals and assistance.
- Employees have access to financial counselling, estate planning and other services in the event of a life-threatening illness or death.
- Adoption Assistance
Amazon offers adoption assistance for qualified domestic and international adoption expenses including attorney fees, court costs, and travel.
- Maternity and Parental Leave
Amazon offers a range of fully paid Maternity and Parental Leave options for parents prior to, and following, the birth or adoption of a child. This includes industry unique “Leave Share” option and a flexible return-to-work program known as “Ramp Back.” Parental options require at least one year of continuous service by the date of a child’s birth or adoption placement.
- Time Off
Regular time away from work is essential for employees to recharge and renew. Employees earn paid time off in addition to company paid holidays.
- BASIC ELIGIBILITIES
A Master’s degree in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
- 4+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
- 1+ years of experience managing a software engineering or machine learning science team.
- Must have delivered features for at least one large-scale production system.
- PhD in Computer Science, Computer Engineering, Mathematics, Statistics, or a related technical field; or equivalent combination of technical education and work experience.
- 6+ years of experience in Applied Machine Learning, Statistics, or a closely-related field.
- 2+ years of experience managing a software engineering or machine learning science team.
- Excellent written and verbal communication skills with the ability to present complex technical information in a clear and concise manner to a variety of audiences.
- A proven track record of hiring and developing software engineers or machine learning scientists.
- A strong sense of curiosity and willingness to learn quickly, building knowledge and skills that this role requires.
- A deep understanding of the software development lifecycle, and a track record of shipping software on time.
- Experience with the Scrum methodology (or similar alternatives) for agile software development.
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
- Deep hands-on technical expertise in cloud-based distributed software design and development, especially utilizing AWS services.
- Knowledge of machine learning approaches and algorithms, and experience building complex highly-scalable systems that involve predictive models or applications of machine learning.
- Ability to handle multiple competing priorities in a fast-paced environment.
Apply through the given link.
Please note that the official organizers have not specified the deadline for this opportunity. Thus, we recommend our users to apply as soon as possible. If you are unsure, please communicate with the official organizers before applying.
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