Amazon

DESCRIPTION

Amazon Q for business is AWS’s generative AI assistant for enterprises. A research engineer at Plato needs to have a strong background in AWS production services, AI, cloud infrastructure, along with a proven track record of delivering results. A research engineer will participate in AI research, develop tooling's and experiment frameworks to improve science team's productivity, interface with engineering team to fill in any gaps, help to gauge science code quality and attend code reviews, manage science on-calls, as well as maintain infrastructures.

Agentic AI drives innovation at the forefront of artificial intelligence, enabling customers to transform their businesses through cutting-edge AI solutions. We build and deliver the foundational AI services that power the future of cloud computing, helping organizations harness the potential of AI to solve their most complex challenges. Join our dynamic team of AI/ML practitioners, applied scientists, software engineers, and solution architects who work backwards from customer needs to create groundbreaking technologies. If you're passionate about shaping the future of AI while making a meaningful impact for customers worldwide, we want to hear from you.

Key job responsibilities

• Participate research and development: direct or indirectly contribute to developing latest Retrieval Augmented Generation technologies, fine-tuning techniques for embedding models and LLMs
• Tool development: build and improve toolings that applied scientists would need, including scalable science experiment frameworks, low-latency testing pipelines, data collection/annotation/evaluation web applications.
• Expedite science to production: bridge the gap between science and engineering teams, help to investigate and mitigate gaps between science and engineering pipeline. Help to merge both pipelines to one, or making components within the two interchangeable. Work towards a fast science-to-production paradigm.
• Science code quality control: serve as gate keeper, review and hold science code quality to production standard
• Manage science infrastructure: act as admin to manage all science AWS account, including patch any security risks, build templates, AWS Cops, conduct cost reduction operations

A day in the life

A Research Engineer supports Applied Scientists in the team by helping to build tools, experiment frameworks, and infrastructures. A Research Engineer may be called to directly facilitate science benchmarking, and deep dive on any deep learning related technical problems. He/she may be called to lead or facilitate a joint project between science and engineering team.

About the team

About AWS

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Diverse Experiences

AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Work/Life Balance

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture

Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Mentorship & Career Growth

We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC QUALIFICATIONS

• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 3+ years of non-internship professional software development experience
• Experience programming with at least one software programming language
• Master's degree or equivalent

PREFERRED QUALIFICATIONS

• 3+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
• Knowledge of professional software engineering & best practices for full software development life cycle, including coding standards, software architectures, code reviews, source control management, continuous deployments, testing, and operational excellence
• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Master's degree in computer science or equivalent
• 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.