Ladders
Machine Learning Engineer II
Skills
14 days ago
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Important information
Contract type:
Permanent
Location:
United States
Work mode:
Remote
Published on:
8 October 2026
What they need
For our client, we are seeking a Machine Learning Engineer II to join the team of a leader in the Consumer Technology space.
This role will focus on building and improving machine learning systems that personalize the user experience at scale. You will partner closely with cross-functional teams to design, test, and deploy models across multiple product areas. The position offers the opportunity to work in a fast-moving environment where rapid experimentation and strong data-driven decision-making directly influence product outcomes.
Location: Remote - US based candidates only, no visa sponsorship available
Compensation: $215,250 – $285,982 annually
Responsibilities
- Build and improve technology that personalizes the user experience using deep learning and machine learning.
- Collaborate with cross-functional teams to experiment with and enhance ML models across multiple product surfaces.
- Use data-driven methods to improve candidate retrieval using unique data properties.
- Contribute in a high-impact environment with rapid experimentation and frequent product launches.
- Stay current on trends in recommendation systems and leverage LLMs for content understanding.
Qualifications
- Master's degree in Computer Science, Data Science, Business Analytics, Engineering, or a related quantitative field.
- Three years of experience in a relevant role or related field.
- Two years of experience in user modeling, personalization, and recommender systems.
- Hands-on experience with data processing pipelines, Hadoop, and Spark.
- Familiarity with deep learning and machine learning advancements.
Benefits
- Full-time telecommuting option available.
- Equity eligibility as part of the compensation package.
- Commitment to an equitable, inclusive, and inspiring workplace culture.
Our client is an equal opportunity employer. We encourage you to apply even if you don’t meet every qualification—your background could be exactly what this team needs.
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