Machine Learning Engineer - Recommendation Systems

Pantera Capital; Palo Alto (CA); On-site; USD 180,000 - 440,000; Full time

Benefits offered by this job

Equity

Medical coverage

Vision coverage

Dental coverage

401(k) retirement plan

Disability insurance

Life insurance

Employee discounts

Job summary

SpaceXAI is seeking exceptional Applied engineers to join a high-priority project used by hundreds of millions of users monthly. You will work at the intersection of advanced AI development and real-world impact, applying your skills to recommendation systems, ranking algorithms, search technologies, and more.

You will design and implement algorithms, utilize SpaceXAI infrastructure, and build data pipelines and training jobs that learn from product data.

Qualifications

• Knowledge of data infrastructure like Kafka, Clickhouse, and Spark.
• Experience building industrial-scale recommender systems or deep learning applications.
• Proficiency with DL frameworks such as JAX or PyTorch.
• CUDA kernel experience is a plus.

Responsibilities

• Designing and architecting recommendation algorithms across various product surfaces
• Leverage SpaceXAI's infra and AI stacks to dramatically enhance the user experience
• Write data pipelines and training jobs that continuously learn from product data.
• Iterate and improve the algorithm by gathering user feedback in real time through experimentation
• Ensuring scalability and efficiency of machine learning systems

Skills

Kafka

Clickhouse

Spark

Recommender systems

DL frameworks (JAX, PyTorch)

CUDA kernels

Job description

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates.

ABOUT THE ROLE:

We’re seeking exceptional Applied engineers to join a high-priority project that approximately 600 million monthly users use. This is an exciting opportunity for individuals with a engineer or scientist background to apply their skills to recommendation systems, ranking algorithms, search technologies, and many other systems. You’ll work at the intersection of advanced AI development and real-world impact, enhancing the ability to connect users with relevant content, accounts, and experiences.

RESPONSIBILITIES:

• Designing and architecting recommendation algorithms across various product surfaces
• Leverage all of SpaceXAI's infra and AI stacks to dramatically enhance the user experience
• Write data pipelines and training jobs that continuously learn from product data.
• Iterate and improve the algorithm by gathering user feedback in real time through experimentation
• Ensuring scalability and efficiency of machine learning systems

BASIC QUALIFICATIONS:

• Knowledge of data infrastructure like Kafka, Clickhouse, and Spark
• Experienced in implementing recommender systems and/or deep learning applications at industrial scale
• Skilled in one or more DL software frameworks such as JAX or PyTorch
• Exceptional candidates may be experienced in writing CUDA kernels

COMPENSATION AND BENEFITS:

$180,000 - $440,000 USD

Base salary is just one part of our total rewards package at SpaceXAI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.

SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.