Member of Technical Staff, Contextual AI

LLM Systems & Performance

$170-200k

Plus equity

Python

CUDA

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

Office located in Mountain View, CA

Context engineering platform for production-grade AI

Open for applications

Context engineering platform for production-grade AI

101-200 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Open for applications

$170-200k

Plus equity

Python

CUDA

PyTorch

Junior, Mid and Senior level

San Francisco Bay Area

Office located in Mountain View, CA

101-200 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Company mission

To change the way the world works through AI.

Job

Company

Role

Who you are

Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or a related technical field (or equivalent practical experience)
Strong programming skills in Python
Experience with at least one major ML framework: PyTorch or JAX
Solid understanding of GPU computing fundamentals (threads/warps/blocks, memory hierarchy, bandwidth vs compute, etc.)
Familiarity with distributed training or inference concepts (e.g., model parallelism, collective communication, disaggregated serving, KV caching)
Interest in performance engineering: profiling, kernel fusion, memory layout, and end-to-end system efficiency
Ability to work in a fast-paced environment, communicate clearly, and collaborate closely with other engineers and researchers

What the job involves

As a a Member of Technical Staff specializing in Research Engineer – LLM Systems & Performance, you will be part of a small, high-impact team building and optimizing LLM systems end-to-end, from Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) pipelines to high-throughput Inference clusters in production
You will collaborate closely with researchers and engineers to develop advanced models and infrastructure for the context layer
Implement and improve components of our SFT and RL training pipelines (e.g., Verl, SkyRL), including data loading, training loops, logging, and evaluation
Contribute to LLM inference infrastructure (e.g., vLLM, SGLang), including batching, KV-cache management, scheduling, and serving optimizations
Profile and optimize end-to-end performance (throughput, latency, compute/memory/bandwidth), using tools like Nsight and profilers to identify and fix bottlenecks
Work with distributed training and inference setups using NCCL, NVLink, and data/tensor/pipeline/expert/context parallelism on multi-GPU clusters
Help experiment with and productionize quantization (e.g., INT8, FP8, FP4, mixed-precision) for both training and inference
Write and optimize GPU kernels using tools like CUDA or Triton, and leverage techniques such as FlashAttention and Tensor Cores where appropriate

Our take

Founded by former Facebook research scientists, Contextual AI is building customizable, scalable and trustworthy Large Language Models for use by enterprises. Its main product is a tool to improve model performance so that users can build production-grade AI systems.

The backbone of this product is a technology that feeds curated information into AI models so that the LLM can have more context and up-to-date information. This helps to minimize AI “hallucinations”, an increasingly common problem for models like ChatGPT.

Contextual AI is currently working with companies in the finance, technology and media sectors. Following its 2024 funding round, the company has gained momentum, most recently announcing the launch of Agent Composer, a product aimed at moving enterprise RAG from experimentation to production ready AI agents.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Aug 2024

$80m

SERIES A

Jun 2023

$20m

SEED

Total funding: $100m

Company benefits

Competitive salary & equity packages
Comprehensive health, dental & vision isnurance
401(k) with employer matching
Support for conference feeds & travel
Team offsites, celebrations & events
Unlimited PTO

Company HQ

Old Mountain View, Mountain View, CA

Leadership

Douwe Kiela

(Co-Founder & CEO)

Previously Adjunct Professor at Stanford University, Head of Research at Hugging Face and Research Scientist at Facebook. Was also the CEO and Founder of Brainstorm IT.

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