Member of Technical Staff, LLM Infrastructure

1 г. назад

175k–220k USD / годСШАLeadHybrid

pythonci/cddistributed systems

Software Engineer for AI Infrastructure focusing on building scalable backend systems for a generative AI platform.

is the platform for specialized intelligence, enabling companies to build, train, and serve AI models tailored to their own data, workflows, and products. Founded by the team behind PyTorch and backed by AMD, Atreides, Benchmark Capital, Index Ventures, Lightspeed, NVIDIA, Sequoia Capital, and TCV, powers production AI with hundreds of state-of-the-art open models across text, image, embedding, audio, and multimodal workloads. Today, is a Series D company valued at $17.5 billion, bringing together an ambitious, collaborative team that's building the future of enterprise AI.
Solve Hard Problems: Tackle challenges at the forefront of AI infrastructure, from low-latency inference to scalable model serving.
Build What’s Next: Work with bleeding-edge technology that impacts how businesses and developers harness AI globally.
Ownership & Impact: Join a fast-growing, passionate team where your work directly shapes the future of AI—no bureaucracy, just results.
Learn from the Best: Collaborate with world-class engineers and AI researchers who thrive on curiosity and innovation.
AI is an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all innovators.

As a Software Engineer on our AI Infrastructure team, you will help design the core systems that power AI’s generative AI platform. You will help build infrastructure and tools that ensure the reliability, performance, quality, and availability of our AI system.
Our mission is to make AI the most reliable and user friendly generative AI platform in the world. You will partner closely with our cloud infrastructure team, product team, and performance team to deliver infrastructure that bridges the gap between our customer and the ultra-performant proprietary inference engine.
Contribute to the design and development of scalable backend infrastructure that supports distributed training, inference, and data pipelines
Build and maintain core backend services such as LLM CI/CD pipeline, control plane, and model serving systems
Support performance optimization, cost efficiency, and reliability improvements across compute, storage, and networking layers
Building frameworks and safeguards to ensure AI has the best model quality in the industry
Collaborate with performance, training, and product teams to translate research and product needs into infrastructure solutions
Participate in code reviews, technical discussions, and continuous integration and deployment processes

Bachelor’s degree in Computer Science, Engineering, or a related technical field (or equivalent practical experience)
3 years of experience in software engineering, with a focus on infrastructure or machine learning systems
Strong programming skills in Python, Go, or a similar language
Proven experience in ML infrastructure and tooling (e.g., PyTorch, MLflow, Vertex AI, SageMaker, Kubernetes, etc.).
Basic understanding of LLM knowledge (e.g., context length, disaggregated prefill, KV cache memory estimation, etc)

5+ years of experience in software engineering, with a focus on infrastructure or machine learning systems
Experience with open source inference engine like vLLM, Sglang, or TRT-LLM
Contributions to open-source infrastructure or ML projects
Experience in building large scale ML/MLOps infrastructure