Amazon
Technology
SoftwareDevelopmentEngineer,MLSystems,AnnapurnaLabs
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Software Development Engineer, ML Systems, Annapurna Labs at Amazon. Skills: Generative AI, ML Systems, AWS Neuron. Research implementations for customers. Improve porting and optimization time”
Industry & Context.
Root cause analysis; Problem solving
What They're Looking For.
Must Have
3+ years software development experience, 2+ years system design experience, Experience programming one language, Computer Science core knowledge, Experience with ML compilers, Experience with production coding agents, Experience with GenAI model architecture, Experience with model training, Experience with neural network optimization, Experience with applied math
Nice to Have
3+ years full SDLC experience, 2+ years ML experience, Experience building AI agents, Experience with open-source communities, Knowledge of state-of-the-art ML
What You'll Do.
Research implementations for customers
Improve porting and optimization time
Solve challenging technical problems
Design innovative software solutions
Implement innovative software solutions
Test innovative software solutions
Deploy innovative software solutions
Maintain innovative software solutions
Build high-quality products
Build highly available products
Build always-on products
Contribute intellectual property
Resolve software defects
Build high-impact solutions
Participate in design discussions
Participate in code review
Communicate with stakeholders
Drive business decisions
Collaborate with compiler engineers
Collaborate with hardware engineers
Collaborate with ML engineers
How You'll Work.
Team & Collaboration
Cross-functional teams; External partners; Internal stakeholders
Communication Scope
Technical input; Stakeholder communication
Process & Methodology
Agile, Scrum
Full Job Description
About the Team The Neuroboros team was recently created to pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs’ location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling. About Amazon Annapurna Labs: Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our AWS customers. We are at the forefront of innovation by combining cloud scale with the world’s most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design, software and operations. Because of our team’s breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances. 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. About AWS Neuron: AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler
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