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AbeBooks

Sr. Machine Learning Engineer, AWS Payments

Location
Canada
Details
Full Time
5 days ago
Job summary
Machine learning, big data; real-time data streaming. If these areas resonate with you, then join us to work on extremely motivating challenges at Amazon Web Services (AWS). Within AWS Payments we build and run Machine Learning models to optimize business processes and improve the customer experience.

If you are a strong software engineer, self-starter and learner who is passionate about working with massive amounts of data to build state-of-art system on top of AWS native services, then this is the right opportunity for you. You will work with a team of highly skilled engineers and scientists, to build the next generation Machine Learning, Data, and Analytics platform at AWS. As part of your job, you will deal with large amounts of training data, rapid prototyping of new models, performance optimizations, offline and online testing, and building fully automated solutions to push Machine Learning models to production, applying MLOps best-practices.

Key job responsibilities
You are fascinated by the power of large scale systems and using machine learning algorithms to optimize decision making. And you're looking for a career where you'll be able to build, to deliver, and to impress. You look at problems holistically, and thrive on the intricate complexity of designing feedback loops and ecosystems. You want to work on projects where you are implementing solutions to real problems that require creative solutions and deep understanding of the problem space. You will partner with research scientists to challenge yourself and others to constantly come up with better solutions. You'll be given an opportunity to own and drive initiatives through the entire software stack -- from customer facing features, to algorithmic innovation, all the way down to the datasets that the back-end services consume.

As a software development engineer of this team, you will play a pivotal role in shaping the definition, vision, design, roadmap and development of this set of product features from beginning to end. You will:
  • Lead the work to define, scope, and plan the engineering workstreams on the team.
  • Meet regularly with scientists, engineers, and product managers from other teams to brainstorm new ideas, identify opportunities for collaboration, and clarify ambiguous problems. This could result in writing project proposals with our collaborators and designing components that have cross-team components.
  • Write clear emails and design documents that convey your work to an audience with varying levels of Software and ML knowledge.
  • Mentor junior engineers through code reviews, design reviews, and tradeoff discussions. Provide valuable feedback.
  • Actively participate in interviewing for Amazon software engineers.
  • Help drive business decisions with your technical input.
  • Design, implement, test, deploy and maintain innovative software solutions, while optimizing service performance, durability, cost, and security.
  • Use software engineering best practices to ensure a high standard of quality for all of the team deliverables.
  • Write high quality distributed and scalable systems, to deal with large scale data.
  • Automate the end-to-end development life-cycle to deploy Machine Learning models from research phase to production.
  • Work in an agile, startup-like development environment, where you are always working on the most important stuff.

In this role you will contribute to a critical and highly-visible function within the AWS business. You will be given the opportunity to autonomously deliver the technical direction of new projects and features in our roadmap. You will work with extraordinary talent and have the opportunity to hire and shape the team to best execute on the product. If you're excited to have a large impact on AWS and the cloud computing industry, you'll find this role to be engaging, challenging, and full of opportunities to learn and grow.

About the team
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.

*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. Amazon's culture of inclusion is reinforced within our 14 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-live 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. This position involves on-call responsibilities, typically for one week every two months. We don't like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don't get paged for the same issue twice.

*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.
Learn more about Amazon on our Day 1 Blog: https://blog.aboutamazon.com/

BASIC QUALIFICATIONS

  • 2+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems
  • 3+ years of programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
  • 4+ years of professional software development experience
  • 2+ years of experience as a mentor, tech lead OR leading an engineering team

  • 5+ years software development experience
  • Strong background and experience in MLOps, Machine Learning, Data Science and related technologies
  • Hands on experience with building data or machine learning pipeline
  • Programming experience with at least one modern language such as Scala, Python, Java.
  • Experience building high-quality scalable production software.
  • Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
  • Bachelor's degree in Computer Science, Computer or Electrical Engineering, Mathematics or a related field.
  • Strong problem solving, debugging and troubleshooting skills.
  • Proficiency with Computer Science fundamentals in object-oriented, data structures, algorithm, problem solving, and complexity analysis.
  • Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.


PREFERRED QUALIFICATIONS

  • 2+ years of experience applying machine learning to solve real-world problems.
  • Experience working with Spark, Hadoop, and AWS (EMR, EC2, S3, SageMaker, etc...)
  • Experience with building high-performance, highly-available and scalable distributed systems.
  • Experience working with large volumes of real-world noisy data.
  • Experience building and operating highly-available online services and fault-tolerant systems.
  • A willingness to dive deep, experiment rapidly and get things done.


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, disability, age, or other legally protected status. If you would like to request an accommodation, please notify your Recruiter.
Category
Software and Programming