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# Machine Learning Senior Software Engineer

- **Company:** Cloud Applications & Technologies Group Inc.
- **Location:** New York, NY, United States
- **Experience:** Expert
- **Salary:** $121,400.0 - $218,600.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Architectural Patterns, Cloud Computing, Cyber Security, Continuous Integration, Python (Programming Language), Machine Learning, Language Modeling, Operational Databases, Inference Optimization, Tensorflow, Akamai, Software Engineering, Scripting, Pytorch, Large Language Models, Model Validation, Discretization, Web Filtering, GGUF, Containerization, AI Platforms, Information Technology, Low Latency, Optimization Algorithms, Transformer Architectures, Data Management, Machine Learning Operations, Vulnerability Analysis
- **Published:** October 3, 2026
- **Apply:** https://www.careerbuilder.com/job-details/machine-learning-senior-software-engineer-new-york-ny--c444916d-d7c2-4631-90b5-fd02b3503599

## About the Role

* Have 5 years of relevant experience and a Bachelor's/Master's degree in Computer Science, Machine Learning, or a related field
 * Demonstrate hands-on experience with modern ML frameworks such as PyTorch, TensorFlow, or JAX, including model training, fine-tuning, and inference optimization
 * Show proficiency in model quantization techniques (GPTQ, AWQ, GGUF) and an understanding of how model compression impacts accuracy and latency
 * Have experience working with large language models (LLMs), transformer architectures, and multi-modal AI systems
 * Demonstrate familiarity with model safety and responsible AI practices, including content filtering, red-teaming, or adversarial robustness evaluation
 * Show proficiency in Python and experience building production data or ML pipelines
 * Have experience with containerized deployments, CI/CD practices, and cloud infrastructure (not required, but suggested)

Work in a way that works for you, Artificial Intelligence (AI), Budgeting, Cloud Computing, Compensation and Benefits, Computer Science, Computer Security, Computer Systems, Content Filtering Software, Data Management, Diversity, Economics, Injections, Machine Learning, Model Validation, Modeling Languages, Performance Metrics, Performance Modeling, Python Programming/Scripting Language, Risk Management, Safety Compliance, Safety Standards, Safety Systems, Sales Closing Skills, Software Development, Software Engineering, System Operations, Team Player, Vulnerability Scanners

## Description

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 Software 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


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