Senior Software Engineer
Company: Akamai
Location: United States (Remote)
Salary: $121,400 - $218,600 a year
Type: Full-time
Remote: Yes
Posted: 2026-03-23
About this role
Do you want to shape how AI models are validated, optimized, and deployed at global scale?
Are you passionate about building the systems that ensure AI models perform reliably and responsibly in production
Join the Akamai Inference Cloud Team!
The Akamai Inference Cloud (AIC) team is part of Akamai's Cloud Technology Group. We design and operate AI platforms enabling customers to run models with unmatched performance, compliance, and economics. This team owns the end-to-end model lifecyclefrom validation and security scanning through quantization, optimization, and monitoring. We ensure every model meets rigorous standards for quality, safety, and performance.
Partner with the best
As an ML Senior Engineer, you will build and operate systems responsible for model validation, quantization, and safety across the AIC. You'll develop pipelines that scan models for vulnerabilities, apply quantization and optimization techniques, and build guardrails that enforce safety and compliance policies. This role requires hands-on ML experience and deep understanding of modern architectures, inference optimization, and responsible
AI.
#AIC
As a Machine Learning Senior Software Engineer, you will be responsible for:
- Developing and maintaining model validation and security scanning pipelines that assess models for quality, correctness, and vulnerabilities prior to deployment
- Implementing quantization, pruning, and other optimization techniques to reduce model footprint and improve inference latency across diverse hardware
configurations
- Building guardrail and content safety systems that enforce compliance policies and mitigate risks such as jail breaking and prompt injection
- Designing model routing and prompt management infrastructure that supports intelligent request handling across model variants
- Contributing to model evaluation frameworks that measure accuracy, performance, and safety metrics across the model lifecycle
**Do what you ...