Remote ML Engineer II: Personalization & Recommender Systems

Ladders; United States; Remote; USD 215,000 - 286,000; Full time

Benefits offered by this job

Telecommuting

Equity

Inclusive culture

Job summary

Our client, a leader in Consumer Technology, is seeking a Machine Learning Engineer II to design, build, and scale personalized experiences for users in a remote US-based role. You will partner closely with cross-functional teams to design, test, and deploy models across multiple product surfaces, leveraging data-driven insight and rapid experimentation.

Compensation is $215,250 – $285,982 annually, with equity eligibility; benefits include telecommuting and a commitment to an inclusive,

Qualifications

• Master's degree required in a quantitative field.
• 3 years of relevant experience.
• 2 years in user modeling/personalization/recommender systems.
• Hands-on data processing with Hadoop and Spark.
• Familiarity with deep learning and ML advancements.

Responsibilities

• Build and improve personalization using deep learning and ML.
• Collaborate with cross-functional teams to experiment with models across product surfaces.
• Use data-driven methods to improve candidate retrieval and content understanding.
• Contribute in a high-impact environment with rapid experimentation and frequent launches.
• Stay current on trends in recommender systems and leverage LLMs.

Skills

Deep learning

Machine learning

Personalization

Recommender systems

Data pipelines

LLMs

Education

Master's degree in Computer Science, Data Science, Engineering, or related quantitative field

Tools

Hadoop

Spark

Job description

Our client, a leader in Consumer Technology, is seeking a Machine Learning Engineer II to design, build, and scale personalized experiences for users in a remote US-based role. You will partner closely with cross-functional teams to design, test, and deploy models across multiple product surfaces, leveraging data-driven insight and rapid experimentation.

Compensation is $215,250 – $285,982 annually, with equity eligibility; benefits include telecommuting and a commitment to an inclusive,