Applied Science Manager, ML Solutions Lab

Key Skills

Java Programming, Python Programming, Framework, SQL, Deep Learning, TensorFlow, R Programming, MxNet

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) and Computer Vision (CV)
Inclusive Team Culture
Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.

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.
The primary responsibilities of this role are to:
 Lead a team of scientists 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

Location flexibility: Open to multiple AWS U.S. West corporate office locations. This position requires travel of up to 20%.

BASIC QUALIFICATIONS

• 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
• 2+ years of experience leading and managing scientists and engineers
• 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

• Practical experience in solving complex problems in an applied environment
• Hands on experience building models with deep learning frameworks like
• MXNet, Tensorflow, or PyTorch, specifically in computer vision
• 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.
• Successful record of developing junior scientists to a successful career track
• Management experience for working on cross-functional projects