Applied Scientist II, Amazon Machine Learning Solution Lab

Key Skills

Java Programming, Leadership, Python Programming, SQL, Machine learning techniques, Deep Learning, Natural Language Processing (NLP), PyTorch, TensorFlow, MxNet, Caffe, RNNs, CNNs

Job Description

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), Computer Vision (CV) and More.

As a ML Solutions Lab Applied Scientist, you are proficient in designing and developing advanced ML models to solve diverse challenges and opportunities. You will be working with terabytes of text, images, and other types of data and develop novel models to solve real-world problems. You'll design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience. You will apply classical ML algorithms and cutting-edge deep learning (DL) and reinforcement learning approaches to areas such as drug discovery, customer segmentation, fraud prevention, capacity planning, predictive maintenance, pricing optimization, call center analytics, player pose estimation, event detection, and virtual assistant among others.

Key job responsibilities

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
• This position requires travel of up to 25%. Role can be preferably based in DC, Maryland, Virginia / New York, New Jersey area; However candidates in Boston or Atlanta area are encouraged to apply.

BASIC QUALIFICATIONS

• PhD (OR master + 4 years) in computer science, engineering, mathematics or related technical/scientific field
• 3+ years of relevant experience in building large scale machine learning or deep learning models and/or systems
• 3+ year of experience specifically with deep learning (e.g., CNN, RNN, LSTM)
• Experience in using Python or other programming languages

PREFERRED QUALIFICATIONS

• PhD degree in computer science, engineering, mathematics, or related technical/scientific field
• Hands on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar
• Experience with machine learning, time series, NLP and CV solutions
• Strong communication and presentation skills
• Strong attention to detail
• 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.