AI Inference Engineer
Job Summary
Job Description
As an AI Inference Engineer, you will be responsible for developing APIs for AI inference that will be used by both internal and external customers. You will benchmark and address bottlenecks throughout our inference stack, improve the reliability and observability of our systems, and respond to system outages. In addition, you will explore novel research and implement LLM inference optimizations. This role involves working on large-scale deployment of machine learning models for real-time inference and requires expertise in ML systems and deep learning frameworks.
Must have:
- Experience with ML systems and deep learning frameworks.
- Familiarity with common LLM architectures and optimization techniques.
- Experience with deploying reliable, distributed, real-time model serving.
Good to have:
- Understanding of GPU architectures or experience with GPU kernel programming using CUDA
Perks:
- Comprehensive health, dental, and vision insurance.
- 401(k) plan
- Equity may be part of the total compensation package.
11 skills required
Job Details
We are looking for an AI Inference engineer to join our growing team. Our current stack is Python, Rust, C++, PyTorch, Triton, CUDA, Kubernetes. You will have the opportunity to work on large-scale deployment of machine learning models for real-time inference.
Responsibilities
- Develop APIs for AI inference that will be used by both internal and external customers
- Benchmark and address bottlenecks throughout our inference stack
- Improve the reliability and observability of our systems and respond to system outages
- Explore novel research and implement LLM inference optimizations
Qualifications
- Experience with ML systems and deep learning frameworks (e.g. PyTorch, TensorFlow, ONNX)
- Familiarity with common LLM architectures and inference optimization techniques (e.g. continuous batching, quantization, etc.)
- Experience with deploying reliable, distributed, real-time model serving at scale
- (Optional) Understanding of GPU architectures or experience with GPU kernel programming using CUDA
At Perplexity, we've experienced tremendous growth and adoption since publicly launching the world's first fully functional conversational answer engine just over a year ago. Our AI-powered search assistant has amassed 10 million monthly active users as of early 2024, with our mobile apps installed over 1 million times across iOS and Android devices. In 2023 alone, we served over 500 million queries from users around the globe.
To support our rapid expansion, we've raised significant funding from some of the most respected investors in technology. In January 2024, we raised $73.6 million in a Series B round led by IVP, with participation from NVIDIA, Jeff Bezos' investment fund, NEA, Databricks, and other prominent firms. We followed that up with a $62.7 million Series B1 round in April 2024 led by Daniel Gross, valuing Perplexity at over $1 billion.
Our prominent investor base includes IVP, NEA, Jeff Bezos, NVIDIA, Databricks, Bessemer Venture Partners, Elad Gil, Nat Friedman, Naval Ravikant, Tobi Lutke, and many other visionary individuals.
Final offer amounts are determined by multiple factors, including, experience and expertise, and may vary from the amounts listed above.
Equity: In addition to the base salary, equity may be part of the total compensation package.
Benefits: Comprehensive health, dental, and vision insurance for you and your dependents. Includes a 401(k) plan.
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