Job details
Salary $114,700 a year job type full-time
Full job description
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
4+ 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
Want to help the largest global enterprises derive business value through the adoption of artificial intelligence (ai) and machine learning (ml)? excited by using massive amounts of disparate data to develop ml models? eager to learn to apply ml to a diverse array of enterprise use cases? thrilled to be a part of amazon who has been pioneering and shaping the world’s ai/ml technology for decades?
At amazon web services (aws), we are helping large enterprises build ml models on the aws cloudWe are applying predictive technology to large volumes of data and against a wide spectrum of problemsAws professional services works together with aws customers to address their business needs using ai solutions.
Aws professional services is a unique consulting teamWe pride ourselves on being customer obsessed and highly focused on the ai enablement of our customersIf you have experience with ai, including building ml models, we’d like to have you join our teamYou will get to work with an innovative company, with great teammates, and have a lot of fun helping our customersA successful candidate will be a person who enjoys diving deep into data, doing analysis, discovering root causes, and designing long-term solutions.
Inclusive team culture
Here at aws, we embrace our differencesWe are committed to furthering our culture of inclusionWe have thirteen employee-led affinity groups, reaching 85,000 employees in over 190 chapters globallyWe have innovative benefit offerings, and host annual and ongoing learning experiences, including our conversations on race and ethnicity (core) and amazecon (gender diversity) conferencesAmazon’s culture of inclusion is reinforced within our 16 leadership principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/life balance
Our team puts a high value on work-life harmonyStriking a healthy balance between your personal and professional life is crucial to your happiness and success hereWe are a customer-obsessed organization—leaders start with the customer and work backwardsThey work vigorously to earn and keep customer trustAs such, this is a customer facing role in a hybrid delivery modelProject engagements include remote delivery methods and onsite engagement that will include travel to customer locations as needed.
Mentorship & career growth
Our team is dedicated to supporting new membersWe have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorshipWe care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.
This is a customer-facing role and you will be required to travel to client locations and deliver professional services as needed.
Major responsibilities include:
Assist customers by being able to deliver a ml project from beginning to end, including understanding the business need, aggregating data, exploring data, building & validating predictive models, and deploying completed models with concept-drift monitoring and retraining to deliver business impact to the organization
Use aws ai services (e.g., personalize), ml platforms (sagemaker), and frameworks (e.g., mxnet, tensorflow, pytorch, sparkml, scikit-learn) to help our customers build ml models
Research and implement novel ml approaches, including hardware optimizations on platforms such as aws inferentia
Work with our other professional services consultants (big data, iot, hpc) to analyze, extract, normalize, and label relevant data, and with our professional services engineers to operationalize customers’ models after they are prototyped
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
Amazon is committed to a diverse and inclusive workplaceAmazon 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 statusFor individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
Pursuant to the san francisco fair chance ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the los angeles fair chance ordinance, we will consider for employment qualified applicants with arrest and conviction records.
For employees based in colorado, this position starts at $114,700 per yearA sign-on bonus and restricted stock units may be provided as part of the compensation package, in addition to a range of medical, financial, and/or other benefits, dependent on the position offered.
