Machine Learning Engineer, AFT AI, Amazon Fulfillment Technologies
vor 2 Monaten
revolutionize Amazon’s Fulfillment network? Are you looking for opportunities
to apply AI on real-world problems at truly vast scale? At Amazon Fulfillment
Technologies and Robotics, we are on a mission to build high-performance
autonomous systems that perceive and act to further improve our world-class
customer experience — at Amazon scale. To this end, we are looking for a
Machine Learning Engineer who will build ML and data infrastructure to support
our science team in training and deploying models that make smarter decisions
on a wide array of multi-modal signals. Together, we will be pushing beyond
the state of the art in optimizing one of the most complex systems in the
world: Amazons Fulfillment Network.
Key job responsibilities
- Responsible for the design, development, and maintenance of scalable ML,
data and annotation infrastructure needed for training, evaluating and
deploying models for real-world applications. Work closely with Applied
Scientists to process massive data, scale machine learning models while
optimizing model performance and efficiency.
- Design and implement software solutions balancing conflicting requirements
of delivery speed, scalability, flexibility, production readiness.
- Work with other team members (Applied Scientists, System Engineers, SDEs,
BIEs, Product and Program Managers) to investigate design approaches,
prototype new technologies and evaluate technical feasibility.
A day in the life
AFT AI delivers the AI solutions that empower Amazon’s fulfillment network to
make smarter decisions. You will work on an interdisciplinary team of
scientists and engineers with deep expertise in developing cutting-edge AI
solutions at scale. You will work on critical MLOps infrastructure for model
training, model inference and data annotation. You will work with product
teams to develop solutions for business problems in the Amazon Fulfillment
Network.
About the team
Amazon Fulfillment Technologies (AFT) powers Amazon’s global fulfillment
network. We invent and deliver software, hardware, and science solutions that
orchestrate processes, robots, machines, and people. We harmonize the physical
and virtual world so Amazon customers can get what they want, when they want
it.
AFT AI is spread across multiple locations in NA (Bellevue WA and Nashville,
TN) and Europe (Berlin, Germany). We are hiring candidates to work out of the
Berlin location.
Publicly available articles showcasing some of our work:
- Damage Detection: https:www.amazon.sciencelatest-newsthe-surprisingly-
subtle-challenge-of-automating-damage-detection
- Product ID: https:www.amazon.sciencelatest-newshow-amazon-robotics-is-
working-on-new-ways-to-eliminate-the-need-for-barcodes
### BASIC QUALIFICATIONS
- Experience (non-internship) in professional software development
- Experience designing or architecting (design patterns, reliability and
scaling) of new and existing systems
- Experience programming with at least one software programming language
- Practical experience with cloud services (e.g. AWS, Microsoft Azure, Google
Cloud)
- Excellent knowledge of MLOps, DataOps and relevant fields
### PREFERRED QUALIFICATIONS
- Masters degree in computer science or equivalent
- Experience with full software development life cycle, including coding
standards, code reviews, source control management, build processes, testing,
and operations
- Experience in deploying deep learning models in production
- Experience with AWS (S3, EC2, CDK, Sagemaker etc.)
- Experience with state-of-the-art deep learning and data science frameworks
like PyTorch, TensorFlow, Pandas
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.jobsenprivacy_page) to know more about
how we collect, use and transfer the personal data of our candidates.
mwd
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