DESCRIPTION
Job summary
Excited to work at cutting edge of Machine Learning (ML) and Internet of Things (IoT)? How does prospect of using massive amounts of data to develop Machine Learning and Deep Learning (DL) models sound? Eager to learn from many different enterprise’s use cases of AWS ML and DL? Thrilled to be key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology?
The problems we solve are real, with tangible customer impact. The work involves working with some of largest global enterprises and help them solve previously unsolved problems with Machine Learning and Artificial Intelligence. We are looking for a passionate and talented Data Scientist who will collaborate with other scientists and engineers to develop computer vision and machine learning methods and algorithms to address real-world customer use-cases. You'll design and run experiments, research new algorithms, and work closely with talented engineers to put your algorithms and models into practice to help solve our customers' most challenging problems.
AWS Professional Services is a unique team. We pride ourselves on being customer obsessed and highly focused on the AI enablement of our customers. We obsess over finding effective and scalable ways to solve customers demanding problems. If you thrive in a fast-paced environment, you’ll meet your match with us, as you will be part of a vibe of constant improvement. We don’t like to sit still, which is why we always treat every day like the first day. A day to make more good things happen for our customers. That's the kind of spirit that drives our success and you could be part of it.
A successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions. It will be a person who likes to have fun, loves to learn, and wants to innovate in the world of AI.
Responsibilities:
· Understand the customer’s business need and guide them to a solution using our AWS AI Services, AWS AI Platforms, AWS AI Frameworks, and AWS AI EC2 Instances .
· Assist customers by being able to deliver a ML / DL project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models to deliver business impact to the organization.
· Use Deep Learning frameworks like MXNet, PyTorch, Caffe 2, Tensorflow, Theano, CNTK, and Keras to help our customers build DL models.
· Work with data architects and engineers to analyze, extract, normalize, and label relevant data.
· Work with our DevOps engineers to help our customers operationalize models after they are built.
· Assist customers with identifying model drift and retraining models.
· Research and implement novel ML and DL approaches, including using FPGA.
This position can have periods of up to 10% travel.
This position requires that the candidate selected be a US Citizen.
BASIC QUALIFICATIONS
- Bachelor’s degree in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.) or equivalent professional or military experience
- Experience with ML fields, e.g., natural language processing, computer vision, statistical learning theory
- 5+ years of industry experience in predictive modeling, data science, and analysis
- Experience in an ML engineer or data scientist role building and deploying ML models or hands on experience developing deep learning models
- Experience writing code in Python, R, Scala, Java, C++ with documentation for reproducibility
- Experience handling terabyte size datasets, diving into data to discover hidden patterns, using data visualization tools, writing SQL, and working with GPUs to develop models
- Experience writing and speaking about technical concepts to business, technical, and lay audiences and giving data-driven presentations
PREFERRED QUALIFICATIONS
- Master’s degree of PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, etc.)
- Ability to develop strategic, baselined, data modeling processes; ability to accurately determine cause-and-effect relationships.
- Publications or presentations in recognized ML journals or conferences
- Deep technical skills, consulting experience, and business savvy to interface with all levels and disciplines within our customers’ organization
- Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
The pay range for this position in Colorado is $130,000-178,000(hr./yr.); however, base pay offered may vary depending on job-related knowledge, skills, and experience. A sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a full range of medical, financial, and/or other benefits, dependent on the position offered. This information is provided per the Colorado Equal Pay Act. Base pay information is based on market location. Applicants should apply via Amazon's internal or external careers site.
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, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Pursuant to the Los Angeles Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Workers in New York City who perform in-person work or interact with the public in the course of business must show proof they have been fully vaccinated against COVID or request and receive approval for a reasonable accommodation, including medical or religious accommodation.