Zefr is a leading global technology company focused on responsible marketing in walled garden social environments.
The company empowers brands to manage content adjacency on platforms like YouTube, Meta, TikTok, and Snap using patented AI technology.
The role involves designing and building large-scale applications and systems to acquire, process, and store multi-terabytes of social media data.
The Machine Learning Engineer will implement infrastructure to support machine learning systems that process hundreds of millions of social media videos daily.
The position requires working with state-of-the-art models, including large language models, to build sophisticated compound AI systems.
The company values a collaborative learning environment where both the employee and the team can learn from each other.
Requirements:
A Bachelor's or Master's degree in Computer Science or a related field with at least 4 years of professional experience is required.
Experience in Machine Learning Operations and Data Engineering is essential.
Fluency in Python and SQL, specifically with Snowflake, is necessary.
Candidates should have experience with distributed systems and machine learning models.
Familiarity with large language models and RAG systems is required.
A strong foundation in data structures, algorithms, and software design is expected.
Candidates must adhere to thorough testing and code review standards and practices.
Strong verbal and written communication skills are essential.
Openness to new technologies and creative solutions is a must.
Benefits:
Employees enjoy flexible PTO and a comprehensive medical, dental, and vision insurance plan with FSA options.
The company provides company-paid life insurance and paid parental leave.
A 401(k) plan with company match is available.
Employees have access to professional development opportunities and 14 paid holidays off.
A flexible hybrid work schedule is offered, along with “Summer Fridays” for shorter workdays during the summer.
In-office lunches and plenty of free food are provided.
Optional in-person and virtual events are organized to celebrate team achievements.
