Sr. Machine Learning Engineer, Global Services Security - Office of Security Innovation

- 6+ years of non-internship professional software development experience
- 6+ years of programming with at least one software programming language experience
- 6+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years experience developing and deploying large-scale machine learning models and/or applications in production, including batch and real-time data processing, model containerization, CI/CD, REST or GraphQL APIs.
- Experience with Python and frameworks such as Pytorch, TensorFlow
- Bachelor's degree in computer science or equivalent
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Hands-on experience building models with deep learning frameworks like MXNet, Tensorflow, Keras, Caffe, PyTorch, or similar. Prior experience training and fine-tuning Large Language Models (LLMs)
- Experience with serverless, event-driven architectures in AWS, including system design, development, and production operations; and infrastructure-as-code using AWS CDK, CloudFormation, or Terraform.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Amazon Web Services is looking for world class software developers with experience in machine learning to join the Security Innovation team in Global Services Security (GSS). AWS GSS is responsible for delivering product-led, people-powered services that help our customers operate their businesses securely on AWS, and we are accelerating our adoption of AI/ML. This is an exciting opportunity to contribute at the intersection of AI/ML, cloud, and cybersecurity.

In this role, you are a passionate, talented, and inventive Software Development Engineer (SDE) with strong experience in ML, including areas such as generative AI, Time Series, Automatic Speech Recognition (ASR), Natural Language Understanding (NLU). Your primary responsibility will be to develop AI/ML solutions to meet the needs of our customers. You will have the opportunity to work with other software developers, data scientists, and internal and external customers alike.

Key job responsibilities
* Work closely with product, engineering, and science teams to design, build, and deploy end-to-end machine learning solutions
* Optimize and scale machine learning models for production environments
* Implement data pipelines and infrastructure for model training and serving
* Collaborate with data scientists and software engineers to integrate ML solutions into applications
* Monitor and maintain deployed ML models and solutions

About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred 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.

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