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Senior Applied Scientist, ML Solutions Lab
Sydney
Full time
I.T., digital & online media services
10,001+ employees
Job summary
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).
The primary responsibilities of this role are to:
Machine learning (ML) has been strategic to Amazon from the early years. We are pioneers in areas such as recommendation engines, product search, eCommerce fraud detection, and large-scale optimization of fulfillment center operations.
The Amazon ML Solutions Lab team helps AWS customers accelerate the use of machine learning to solve business and operational challenges and promote innovation in their organization. We are looking for a passionate, talented, and inventive Applied Scientist with a strong machine learning background to help develop solutions by pushing the envelope in Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU), Machine Learning (ML) and Computer Vision (CV).
The primary responsibilities of this role are to:
- Design, develop, and evaluate innovative ML/DL models to solve diverse challenges and opportunities across industries
- Interact with customer directly to understand their business problems, and help them with defining and implementing scalable ML/DL solutions to solve them
- Work closely with account teams, research scientist teams, and product engineering teams to drive model implementations and new algorithms
BASIC QUALIFICATIONS
- Graduate degree (MS or PhD) in computer science, engineering, mathematics or related technical/scientific field
- 5+ years of professional experience in a business environment
- 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
- Sound theoretical understanding of broad machine learning concepts, with deep and demonstrable expertise in at least one topic or application of machine learning
- Strong coding and problem-solving skills in Python and other programming languages
PREFERRED QUALIFICATIONS
- PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field
- Practical experience in solving complex problems in an applied environment
- Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar
- Strong communication skills, with attention to detail and ability to convey rigorous mathematical concepts and considerations to non-experts
- Comfortable working in a fast paced, highly collaborative, dynamic work environment
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field