Applied Scientist - AWS ML Platforms, SageMaker Clarify

Berlin, Berlin, DEU

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Job summary
Interested in machine learning and AI? Can you envision a future where technology is driven primarily by smarter machines?

The mission of AWS AI is to make machine learning easy, fast, and universal across all of our customers. Our world class platform provides the services that runs 85% of all on-cloud machine learning through performance optimizations, machine learning tools, and SDKs to democratize machine learning. Our customers include scientists, data analysts, and ML engineers all building and deploying models through either SageMaker or self-managed instances on EC2/EKS.

The AWS Machine Learning Services group in Amazon AI is seeking applicants for an Applied Scientist position in the areas of fairness, bias, explainability, privacy, and model understanding in ML. As an Applied Scientist in AWS AI, you will be driving many scientific breakthroughs to help our customers understand and trust ML-based outcomes, and also working with software engineers to deploy these solutions to AWS customers. You will be working on the ML platforms and services that power over 85% of machine learning in the cloud, and help make machine learning fast, accessible, universal, and trustworthy for all our customers.

We look for candidates with a PhD in a relevant technical field (such as Algorithms, Machine Learning, AI, and Mathematics), preferably with interest / experience in explainability, fairness, privacy, and model understanding. We also encourage graduating PhD students as well as recent PhD graduates to apply. You will be working closely with software engineers so experience with cloud systems is a benefit. Our customers are deeply technical and the solutions we build for them are strongly coupled to technical feasibility. You must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means you are not only able to develop and drive high-level strategic initiatives, but can also roll up your sleeves, dig in and get the job done. Ownership, high judgment, negotiation skills, ability to influence, analytical talent and leadership are essential to success in this role. For more information about AWS AI team, please see https://aws.amazon.com/machine-learning and https://aws.amazon.com/sagemaker.

As an Applied Scientist you are expected be an expert in an area relevant for large scale machine learning and its applications. Your position will require you to:
· Work directly with software engineers to develop new products within AWS
· Improve and accelerate our technology with science, statistical modeling, algorithm design, and prototyping
· Maintain an understanding of industry and technology trends in said area of research
· Contribute to Amazon's Intellectual Property through patents and external publications
· Understand business context to decisions made within and across groups

About Us
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.





Basic Qualifications


· Completed PhD, or progress towards a completed PhD degree with specialization machine learning/deep learning, algorithms, mathematics, and related fields
· Experience in using Python, R or Matlab or other statistical/machine learning software language
· Experience with machine learning/deep learning frameworks (TensorFlow, PyTorch, MXNet) and related libraries
· Knowledge and practical experience in several areas of machine learning, including: Classic ML, Deep Learning systems, NLP, Computer Vision, or similar
· Proven publication record at top conferences and journals

Preferred Qualifications

· 3+ years of professional experience in the field
· Experience specifically with deep learning (e.g., CNN, RNN, LSTM, etc.)
· Experience working effectively with software engineering teams
· Proven written and verbal communication skills


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. Protecting your privacy and the security of your data is a longstanding top priority for Amazon. Please consult our Privacy Notice (https://www.amazon.jobs/en/privacy_page) to know more about how we collect, use and transfer the personal data of our candidates.

m/w/d

Job perks/benefits: Career development Conferences
Job region(s): Europe
Job stats:  4  0  0
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