Degree in Artificial intelligence- AI
Degree in Natural Language Processing- NLP
Aartificial intelligence, C++, Deep Learning, Java Programming, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Python Programming, R Programming, Scikit-learn, SPARK Programming
Key job responsibilities
As a Sr. Applied Scientist, you will be mapping business problems to high-impact solutions with focus on language models. You will turn theoretically sound ML/AI methods into practically applicable models designed for processing massive volumes of data in large-scale environments. You will define business-relevant solutions implemented as end-to-end ML/AI functions that integrate with our partners' production systems. You dive deep into all aspects of the practical machine learning development cycle, encompassing sound use of data pre-processing techniques, analysis, modelling, and validation methods. You master the complex theory under the hood of machine learning and you keep up to date with the latest scientific development in information processing, modelling, and learning methods. You take lead of the scientific and technical work in cross-team collaborations with the ultimate objective of creating a delightful experience for our customers using our solutions.
A day in the life
In a fast-paced innovation environment, you work together with our scientists and ML-engineers. You develop and deploy experiments and models at scale. You develop science initiatives with long-term impact on the business. You dive deep into practically challenging science problems, enabling ML/AI-driven automation, insights, and user experiences together with our internal partners. You work close to production to understand our customers' challenges. Sometimes you help out with operational excellence. You mentor science peers and interns, and you take part in educating our org in scientific best practices.
About the team
We work back to back to address the technical challenges of automation, service resilience, and operational efficiency across a variety of products, softwares, and systems. Our scientists and machine learning engineers work in synergy to solve hard problems, enriching each other's skills. Together, we are a powerful team of specialists in EU and NA bringing the potential of practical ML and AI to the max with impact on millions of Amazon customers.
We are open to hiring candidates to work out of one of the following locations:
Vancouver, BC, CAN
BASIC QUALIFICATIONS
- Experience with neural deep learning methods and machine learning
- 4+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- PhD in computer science, machine learning, operations research, statistics, mathematics (or equivalent field)
PREFERRED QUALIFICATIONS
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with conducting research in a corporate setting
- Specialist competence in natural language processing
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Amazon.com, Inc. is an American multinational technology company with operations in cloud computing, streaming media, artificial intelligence, and e-commerce. The company has been referred to as one of the most influential economic and cultural forces in the world, and it is one of the world's most valuable brands.
Vancouver, BC, Canada
2-4 year
Toronto, ON, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Toronto, ON, Canada
2-4 year
Vancouver, BC, Canada
2-4 year
Berlin, Germany
2-4 year
Arlington, VA, USA
2-4 year
Austin, TX, USA
2-4 year
Bellevue, WA, USA
2-4 year
California City, CA, USA
2-4 year
Newark, NJ, USA
2-4 year
Newark, NJ, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Sumner, WA, USA
2-4 year
Seattle, WA, USA
2-4 year
Mumbai, Maharashtra, India
2-4 year
Berlin, Germany
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
New York, NY, USA
2-4 year
Westborough, MA, USA
0-2 year
Arlington, TX, USA
2-4 year
Seattle, WA, USA
6-8 year
Sunnyvale, CA, USA
6-8 year
New York, NY, USA
6-8 year
Seattle, WA, USA
4-6 year
Palo Alto, CA, USA
0-2 year
New York, NY, USA
0-2 year
Seattle, WA, USA
0-2 year
Arlington, VA, USA
0-2 year
New York, NY, USA
4-6 year
Arlington, VA, USA
4-6 year
Seattle, WA, USA
4-6 year
San Diego, CA, USA
4-6 year
Irvine, CA, USA
4-6 year
San Francisco, CA, USA
4-6 year
Brisbane QLD, Australia
0-2 year
Adelaide SA, Australia
0-2 year
Canberra ACT, Australia
0-2 year
Vancouver, BC, Canada
2-4 year
San José Province, San José, Costa Rica
0-2 year
Palo Alto, CA, USA
0-2 year
Seattle, WA, USA
0-2 year
Vancouver, BC, Canada
2-4 year
Toronto, ON, Canada
0-2 year
Seattle, WA, USA
8-10 year