Member of Technical Staff - Recommendation Systems

USD 180,000-440,000 per year

MIDDLE SENIOR

✅ On-site

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI @ 6 Algorithms @ 6 CUDA @ 8 ClickHouse @ 3 Data Pipelines Deep Learning @ 3 Experimentation JAX @ 5 Kafka @ 3 Machine Learning PyTorch @ 5 Spark @ 3

Details

SpaceXAI is seeking exceptional applied engineers to work on a high-priority project used by approximately 600 million monthly users. The role focuses on recommendation systems, ranking algorithms, search technologies, and related systems, applying advanced AI development to connect users with relevant content, accounts, and experiences.

Responsibilities

Design and architect recommendation algorithms across various product surfaces.
Leverage SpaceXAI's infrastructure and AI stacks to enhance the user experience.
Write data pipelines and training jobs that continuously learn from product data.
Iterate on and improve algorithms by gathering real-time user feedback through experimentation.
Ensure the scalability and efficiency of machine learning systems.

Requirements

Knowledge of data infrastructure such as Kafka, ClickHouse, and Spark.
Experience implementing recommender systems and/or deep learning applications at industrial scale.
Proficiency with one or more deep learning software frameworks, such as JAX or PyTorch.
Exceptional candidates may have experience writing CUDA kernels.