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Tue Jun 25 2024
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Machine Learning Scientist, Syne Tune

Amazon Web Services (AWS)

Germany (Berlin) Hybrid


Employment Type: Full-time
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Job Description

We are looking for a Senior Applied Scientist who is passionate about building services and tools for developers that leverage artificial intelligence and machine learning. You will be part of a team building Large Language Model (LLM)-based services with the focus on enhancing the developer experience in the Cloud. The team works in close collaboration with other AWS services such as AWS Cloud9, the AWS IDE Toolkit and AWS Bedrock. If you are excited about working in cloud computing and building new AWS services, then we'd love to talk to you.

As a Senior Machine Learning Scientist, you are recognized for your expertise, advise team members on a range of machine learning topics, and work closely with software engineers to drive the delivery of end-to-end modeling solutions. Your work focuses on ambiguous problem areas where the business problem or opportunity may not yet be defined. The problems that you take on require scientific breakthroughs.

You take a long-term view of the business objectives, product roadmaps, technologies, and how they should evolve. You drive mindful discussions with customers, engineers, and scientist peers. You bring perspective and provide context for current technology choices, and make recommendations on the right modeling and component design approach to achieve the desired customer experience and business outcome.

Key job responsibilities

  • Research and implement novel approaches in the area of active learning, meta-learning, continual learning, automatic machine learning and/or Bayesian decision making.
  • Understand the challenges that developers face when building software today, and develop generalizable solutions.
  • Collaborate with developers and pave the way towards bringing your solution into production systems. Lead cross team projects and ensure technical blockers are resolved
  • Communicate and document your research via publishing papers in external scientific venues.

A day in the life
Work/Life Harmony: Our team gives high value to work-life harmony. Since the Covid19 pandemic we adjusted to remote work and since then have established a hybrid work environment in which team members spend 3 days working in the office.

Mentorship & Career Growth: We're committed to the growth and development of every member of the team. As a Senior Applied Scientist you will play a vital part in growing your peers. You will have the opportunity to contribute to the culture and direction and deliver site-wide initiatives that will improve the life of all of our teams.

About The Team
You will work on the Amazon Web Services (AWS) Next Gen Dev Experience (NGDE) team where we use generative AI and foundation models to reimagine the experience of builders on AWS.

You will work closely with Flock, an internal developer toolkit for AWS teams building and operating generative AI features on top of AWS Bedrock. Flock components embed our latest learnings and best practices on how to leverage large LLMs so that AWS teams can build new generative AI features faster, more securely, and with higher quality.

Utility Computing (UC)
AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (Iot), Platform, and Productivity Apps services in AWS. Within AWS UC, Amazon Dedicated Cloud (ADC) roles engage with AWS customers who require specialized security solutions for their cloud services.

About AWS

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.

Why AWS?
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.

Inclusive Team Culture
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.

Mentorship & Career Growth
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.

Work/Life Balance
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.

We are open to hiring candidates to work out of one of the following locations: Berlin, BE, DEU
Basic Qualifications

  • PhD degree with specialization machine learning/deep learning, algorithms, mathematics, and related fields.
  • Experience with machine learning/deep learning frameworks (TensorFlow, PyTorch, MXNet) and related libraries.
  • 3+ years of professional experience in the field.
  • Experience working effectively with software engineering teams.
  • Excellent written and verbal communication skills.
  • Strong publication record at top conferences(NeurIPS, ICML, ICLR, AISTATS) or journals like JMLR.

Preferred Qualifications

  • Experience in AutoML: hyperparameter optimization, meta learning, automated decision making.
  • Experience in modeling natural text with transformer networks, specifically large language models.
  • Excellent written and verbal communication skills.
  • 5+ years of professional experience in the field.

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 ( to know more about how we collect, use and transfer the personal data of our candidates.


Company - Amazon Web Services Development Center Germany GmbH - R28

Job ID: A2512656

Apply for this job
🍀 Please mention you found the job on EU Data Jobs. It helps us reach out to more companies. We wish you lots of success! 🍀

About the Company

Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing. The ultimate benefit of cloud computing, and AWS, is the ability to leverage a new business model and turn capital infrastructure expenses into variable costs. Businesses no longer need to plan and procure servers and other IT resources weeks or months in advance. Using AWS, businesses can take advantage of Amazon's expertise and economies of scale to access resources when their business needs them, delivering results faster and at a lower cost.

Today, Amazon Web Services provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world. With data center locations in the U.S., Europe, Singapore, and Japan, customers across all industries are taking advantage of our low cost, elastic, open and flexible, secure platform.


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