Machine Learning Engineer - Recommendation Systems

SpaceXSI is hiring applied engineers to help build recommendation systems and ranking/search technologies for a high-priority product serving around 600 million monthly users. The role is based in Palo Alto, CA (onsite), with compensation ranging from $180,000 to $440,000 USD per year. You will use SpaceXSI’s infrastructure and AI stack to improve user experiences through continuous learning and real-time experimentation.

What you’ll build

You will design and architect recommendation algorithms across multiple product surfaces. The goal is to create systems that learn from product behavior, deliver relevant experiences at scale, and keep improving as new data arrives.

Responsibilities

• Design and architect recommendation algorithms across different product surfaces
• Leverage SpaceXSI infrastructure and AI stacks to improve the user experience
• Write data pipelines and training jobs that continuously learn from product data
• Iterate using real-time experimentation to gather user feedback and refine model performance
• Ensure machine learning systems are scalable and efficient

Requirements

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

Tools you’ll work with

• Kafka, Clickhouse, Spark
• JAX, PyTorch
• CUDA

Compensation and benefits

• Equity
• Comprehensive medical, vision, and dental coverage
• 401(k) retirement plan access
• Short-term and long-term disability insurance
• Life insurance
• Various other discounts and perks

Compensation: $180,000 - $440,000 USD per year