Machine Learning Engineer, AI Research & Education

Key Skills

Java Programming, Analytical and Problem solving, Design, Python Programming, C++, Framework, SQL, Data science techniques, Deep Learning, NumPy, PyTorch, SciPy, TensorFlow, Scikit-learn, MxNet, Amazon Elastic Compute Cloud-EC2, AWS Sagemaker, Amazon Simple Storage Service (S3), C# Programming, Mathematics, JAX framework

Job Description

AWS AI/ML is looking for world class engineers to join its AI Research and Education group working on building open-source automated ML solutions. Our team’s mission is to democratize machine learning by creating powerful open-source tools like AutoGluon for solving practical ML problems and revolutionize the rate and ease ML practitioner’s progress from problem formulation to deployed solution. Our vision is to advance the state-of-the-art in automated ML to become the go-to tool for solving the vast majority of ML problems. The team specializes in developing popular open-source software libraries like AutoGluon, GluonCV, GluonNLP, and Deep Graph Library (DGL). Building these solutions requires a solid foundation in machine learning infrastructure and deep learning technologies.

As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge (around machine learning, natural language processing, computer vision), technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of the AutoGluon framework via collaboration with the open-source, academic and research communities. You will be at the heart of a growing and exciting focus area for AWS and work with other acclaimed engineers and world famous scientists. You will have the opportunity to publish in scientific conferences and journals, create white papers, write blogs, and have high visibility in the industry.

About the team

Inclusive Team Culture

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-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. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded scientist and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• 4+ years of professional software development experience
• 3+ years of programming experience with at least one software programming language
• 2+ years of experience contributing to the system design or architecture (architecture, design patterns, reliability and scaling) of new and current systems
• Experience as a mentor, tech lead OR leading an engineering team

• B.S. degree in Computer Science and Engineering, Electrical Engineering, Mathematics, or related disciplines.
• 3+ years of professional programming experience with Python and at least one modern language such as Java, C++, or C# including object-oriented design.
• 3+ years of software development experience in high performance computing, networking, hardware optimization, distributed training, systems architecture, machine learning, deep learning, ML Ops, or related areas.
• Experience with data science tools such as scikit-learn, Pandas, Numpy, SciPy.
• Excellent problem solving ability
• Strong verbal and written communication skills

PREFERRED QUALIFICATIONS

• M.S. degree or Ph.D. degree in Computer Science and Engineering, Electrical Engineering, Mathematics, or related disciplines.
• Experience with deep learning frameworks such as PyTorch, TensorFlow, JAX, MXNet.
• Hands-on experience with AWS services such as SageMaker, S3, and EC2.
• Practical experience in areas including: ML competitions, open-source software development, and ML benchmarking.