Senior Site Reliability Engineer, AI Inference

Reposted 3 Days Ago
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Dublin, IRL
In-Office
Senior level
Cloud • Information Technology • Security • Software
The Role
The AI Inference Engineer optimizes Large Language Models for inference in diverse environments, ensuring high performance and reliability through optimized deployment, hardware acceleration, and scalable architecture.
Summary Generated by Built In

At F5, we strive to bring a better digital world to life. Our teams empower organizations across the globe to create, secure, and run applications that enhance how we experience our evolving digital world. We are passionate about cybersecurity, from protecting consumers from fraud to enabling companies to focus on innovation. 
 

Everything we do centers around people. That means we obsess over how to make the lives of our customers, and their customers, better. And it means we prioritize a diverse F5 community where each individual can thrive.

Job Title: AI Inference Engineer 

 

Role Objective 

The AI Inference Engineer plays a critical role in the AI lifecycle by bridging the gap between high-performance model development and optimized deployment environments. This position focuses on optimizing Large Language Models (LLMs) for inference, serving diverse environments—from GPU-rich data centers to resource-constrained edge devices—with a strong emphasis on maximizing throughput, minimizing latency, and maintaining model accuracy.  

This role is pivotal in advancing F5’s AI capabilities, ensuring enterprise-grade reliability by leveraging hardware acceleration, designing scalable infrastructure, and monitoring system performance. 

 

Key Responsibilities 

High-Performance AI Serving 

  • Build and maintain robust inference engines using tools like vLLM, TGI (Text Generation Inference), and NVIDIA Triton, ensuring high performance at scale.  

  • Handle deployment optimizations to deliver low-latency AI serving solutions for multiple business applications. 

Hardware Acceleration and Optimization 

  • Profile and optimize models for specialized hardware backends, including NVIDIA GPUs (CUDA/TensorRT), Apple Silicon (CoreML), and AI accelerators like TPUs and LPUs 

  • Collaborate with hardware teams to maximize utilization and performance across various computational environments. 

Inference Orchestration and Scalability 

  • Design and implement auto-scaling architectures for online (real-time) and batch inference pipelines, leveraging Kubernetes for inference routing and orchestration.  

  • Ensure software solutions are optimized for peak performance during traffic spikes, maintaining reliability and scalability. 

Performance Monitoring and Observability 

  • Establish robust observability frameworks to monitor Time to First Token (TTFT), tokens per second, and memory bandwidth utilization against service-level agreements (SLAs).  

  • Build and execute performance and load testing suites to identify bottlenecks and ensure consistent reliability at scale. 

 

Technical Requirements 

Required Skills: 

  • Programming Languages: Proficiency in programming languages such as Python, C++, Rust, or Golang specifically for high-performance AI workflows.  

  • Inference Tools: Proven hands-on experience with tools like vLLM, TensorRT, Llama.cpp, and Ollama for inference development and optimization.  

  • Infrastructure Expertise: Strong familiarity with infrastructure technologies, including Docker, Kubernetes, and cloud platforms such as AWS, GCP, and Azure 

  • Hardware Optimization Expertise: Comprehensive understanding of GPU and AI hardware, including techniques for profiling and optimizing performance for accelerators like NVIDIA GPUs and TPUs. 

 

Preferred Experience: 

  • Prior experience deploying Large Language Models (LLMs) with advanced techniques like Speculative Decoding or PagedAttention 

  • Contributions to open-source inference libraries or hardware-level kernel development (e.g., CUDA, Triton kernels).  

  • Background in MLOps or SRE roles focused on high-performance AI endpoints and reliability during demand surges.  

  • Proficiency in designing scalable solutions for high-throughput inference environments optimized for traffic bursts. 

 

Success Metrics (KPIs): 

  • Latency Reduction: Continuously improve inference latency metrics, ensuring minimal Time to First Token (TTFT) and maximum tokens per second.  

  • Cost Efficiency: Achieve lower "Cost per 1K Tokens" through better resource utilization and hardware optimization.  

  • Scalability: Maintain system stability and reliability during traffic spikes, ensuring performance consistency across environments.  

  • Throughput Maximization: Deploy models optimized for peak hardware usage and maximized process throughput. 

 

Why Join F5? 

F5 empowers you to push boundaries in AI optimization and high-performance engineering. Joining our team means:  

  • Collaborating with cutting-edge technologies and hardware solutions to support real-time AI applications.  

  • Advancing your career in a fast-paced, multidisciplinary environment focused on innovation, scalability, and problem-solving.  

  • Driving transformative projects that deliver real-time AI reliability to global customers while maintaining cost and efficiency standards.  

  • Working on advanced MLOps solutions that seamlessly scale enterprise AI systems and shape the future of intelligent deployment. 

 

What Success Looks Like: 

As an AI Inference Engineer at F5, success is measured by your ability to:  

  • Combine technical expertise and problem-solving skills to deliver low-latency, scalable, and high-performing AI prediction systems.  

  • Collaborate efficiently across cross-functional teams, participating in knowledge sharing and system refinement.  

  • Demonstrate initiative by driving optimizations across hardware, tools, and orchestration processes, balancing immediate solutions with long-term architectural goals.  

  • Translate complex AI and inference workflows into practical solutions that align with F5's strategic objectives. 

 

The Job Description is intended to be a general representation of the responsibilities and requirements of the job. However, the description may not be all-inclusive, and responsibilities and requirements are subject to change.

Please note that F5 only contacts candidates through F5 email address (ending with @f5.com) or auto email notification from Workday (ending with f5.com or @myworkday.com).

Equal Employment Opportunity

It is the policy of F5 to provide equal employment opportunities to all employees and employment applicants without regard to unlawful considerations of race, religion, color, national origin, sex, sexual orientation, gender identity or expression, age, sensory, physical, or mental disability, marital status, veteran or military status, genetic information, or any other classification protected by applicable local, state, or federal laws. This policy applies to all aspects of employment, including, but not limited to, hiring, job assignment, compensation, promotion, benefits, training, discipline, and termination.  F5 offers a variety of reasonable accommodations for candidates. Requesting an accommodation is completely voluntary. F5 will assess the need for accommodations in the application process separately from those that may be needed to perform the job. Request by contacting [email protected].

Skills Required

  • Proficiency in programming languages such as Python, C++, Rust, or Golang specifically for high-performance AI workflows
  • Experience with tools like vLLM, TensorRT, Llama.cpp, and Ollama for inference development and optimization
  • Familiarity with infrastructure technologies, including Docker, Kubernetes, and cloud platforms such as AWS, GCP, and Azure
  • Comprehensive understanding of GPU and AI hardware, including techniques for profiling and optimizing performance for accelerators like NVIDIA GPUs and TPUs

F5 Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about F5 and has not been reviewed or approved by F5.

  • Equity Value & Accessibility Equity grants and an employee stock purchase plan are positioned as meaningful parts of total compensation, with RSUs and a discount ESPP commonly included. Pay packages for many technical roles are considered competitive when equity is taken into account.
  • Leave & Time Off Breadth Paid vacation that increases with tenure, sick time, paid holidays, and paid family leave are prominently featured. Additional programs like volunteer time and periodic wellness long weekends are highlighted as part of the time-off ecosystem.
  • Inclusive Benefits Coverage Health plans include travel support for specific care (such as reproductive and gender‑affirming services) and mental health resources, alongside comprehensive medical, dental, and vision coverage. These elements are presented as part of a broad, inclusive approach to healthcare.

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The Company
HQ: Seattle, WA
5,847 Employees

What We Do

F5 application services ensure that applications are always secure and perform the way they should—in any environment and on any device. F5 (NASDAQ: FFIV) powers applications from development through their entire life cycle, across any multi-cloud environment, so our customers – enterprise businesses, service providers, governments, and consumer brands—can deliver differentiated, high-performing, and secure digital experiences.

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