Role at a glance
- Salary
- Not Disclosed
- Location
- London, UK United Kingdom - England - London
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 4+ years of experience building large-scale, high-performance backend systems.
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Role Summary
The Software Engineer on the ML Infrastructure team designs and builds platforms for scalable, reliable, and efficient serving of LLMs and other models. The platform supports research and production systems across internal and external use cases, while the role bridges research and engineering to deliver customer experiences and accelerate innovation.
What You'll Do
- Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale.
- Build an internal platform to empower LLM capability discovery.
- Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
- Conduct architecture and design reviews to uphold best practices in system design and scalability.
- Develop monitoring and observability solutions to ensure system health and performance.
- Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment.
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Strong ML fundamentals; deep expertise in backend system design; strong programming skills in one or more of Python, Go, Rust, or C++; experience with LLM serving and routing fundamentals, LLM capabilities and concepts, containers and orchestration tools, cloud infrastructure, and infrastructure as code; ability to solve complex problems and work independently.
Required
- Strong ML fundamentals
- Deep expertise in backend system design
- Strong programming skills in one or more languages, including Python, Go, Rust, or C++
- Experience with LLM serving and routing fundamentals, including rate limiting, token streaming, load balancing, and budgets
- Experience with LLM capabilities and concepts such as reasoning, tool calling, and prompt templates
- Experience with containers and orchestration tools such as Docker and Kubernetes
- Familiarity with cloud infrastructure such as AWS and GCP
- Familiarity with infrastructure as code such as Terraform
Preferred
- Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference
Original job description
Content provided by the employer
Original job description
Content provided by the employer
As a Software Engineer on the ML Infrastructure team, you will design and build platforms for scalable, reliable, and efficient serving of LLMs. Our platform powers cutting-edge research and production systems, supporting both internal and external use cases across various environments.
The ideal candidate combines strong ML fundamentals with deep expertise in backend system design. You’ll work in a highly collaborative environment, bridging research and engineering to deliver seamless experiences to our customers and accelerate innovation across the company.
You will:
- Build and maintain fault-tolerant, high-performance systems for serving LLMs and other models at scale.
- Build an internal platform to empower LLM capability discovery.
- Collaborate with researchers and engineers to integrate and optimize models for production and research use cases.
- Conduct architecture and design reviews to uphold best practices in system design and scalability.
- Develop monitoring and observability solutions to ensure system health and performance.
- Lead projects end-to-end, from requirements gathering to implementation, in a cross-functional environment.
Ideally you'd have:
- 4+ years of experience building large-scale, high-performance backend systems.
- Strong programming skills in one or more languages (e.g., Python, Go, Rust, C++).
- Experience with LLM serving and routing fundamentals (e.g. rate limiting, token streaming, load balancing, budgets, etc.)
- Experience with LLM capabilities and concepts such as reasoning, tool calling, prompt templates, etc.
- Experience with containers and orchestration tools (e.g., Docker, Kubernetes).
- Familiarity with cloud infrastructure (AWS, GCP) and infrastructure as code (e.g., Terraform).
- Proven ability to solve complex problems and work independently in fast-moving environments.
Nice to haves:
- Experience with modern LLM serving frameworks such as vLLM, SGLang, TensorRT-LLM, or text-generation-inference.
PLEASE NOTE: Our policy requires a 90-day waiting period before reconsidering candidates for the same role. This allows us to ensure a fair and thorough evaluation of all applicants.
About Us:
At Scale, our mission is to develop reliable AI systems for the world's most important decisions. Our products provide the high-quality data and full-stack technologies that power the world's leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. We work closely with industry leaders like Meta, Ernst & Young, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force. We are expanding our team to accelerate the development of AI applications.
We believe that everyone should be able to bring their whole selves to work, which is why we are proud to be an inclusive and equal opportunity workplace. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability status, gender identity or Veteran status.
We are committed to working with and providing reasonable accommodations to applicants with physical and mental disabilities. If you need assistance and/or a reasonable accommodation in the application or recruiting process due to a disability, please contact us at [email protected]. Please see the United States Department of Labor's Know Your Rights poster for additional information.
We comply with the United States Department of Labor's Pay Transparency provision.
PLEASE NOTE: We collect, retain and use personal data for our professional business purposes, including notifying you of job opportunities that may be of interest and sharing with our affiliates. We limit the personal data we collect to that which we believe is appropriate and necessary to manage applicants’ needs, provide our services, and comply with applicable laws. Any information we collect in connection with your application will be treated in accordance with our internal policies and programs designed to protect personal data. Please see our privacy policy for additional information.
About the company
Scale AI
Large Enterprise
Scale AI is a leading provider of data-centric AI solutions that empower businesses to accelerate their artificial intelligence initiatives. Founded in 2016, the company specializes in offering high-quality training data for machine learning models, helping organizations effectively harness the power of AI across various industries. Scale AI leverages innovative technology and a skilled workforce to deliver precise data labeling services and streamline data workflows, ensuring clients can achieve greater efficiencies and improved outcomes in their AI projects. With a commitment to innovation and quality, Scale AI is positioned as a key partner for companies looking to integrate AI into their operations.
Scale AI is a leading provider of data-centric AI solutions that empower businesses to accelerate their artificial intelligence initiatives. Founded in 2016, the company specializes in offering high-quality training data for machine learning models, helping organizations effectively harness the power of AI across various industries. Scale AI leverages innovative technology and a skilled workforce to deliver precise data labeling services and streamline data workflows, ensuring clients can achieve greater efficiencies and improved outcomes in their AI projects. With a commitment to innovation and quality, Scale AI is positioned as a key partner for companies looking to integrate AI into their operations.