<p><strong>***For immediate response please email Valerie Nielsen***</strong></p><p><br></p><p><strong>Job Title:</strong> Machine Learning Engineer / Data Engineer</p><p> <strong>Location:</strong> Culver City, CA (Onsite 4 days per week)</p><p> <strong>Compensation:</strong> $200,000 Base + Bonus/Equity (if applicable)</p><p><strong>Overview</strong></p><p> We are seeking a <strong>Machine Learning Engineer / Data Engineer</strong> to help build scalable data and machine learning platforms that power intelligent products and decision systems. This role will focus on developing infrastructure and pipelines that enable multiple teams to leverage advanced analytics, real-time decisioning, and modern AI capabilities including LLM-based applications.</p><p>The ideal candidate has experience building <strong>data and ML platforms used across an organization</strong>, and enjoys working at the intersection of <strong>data engineering, machine learning infrastructure, and production AI systems</strong>.</p><p><strong>Responsibilities</strong></p><ul><li>Design and build <strong>scalable data and machine learning platforms</strong> used by multiple internal teams</li><li>Develop and maintain <strong>ML pipelines, feature stores, and training workflows</strong></li><li>Build infrastructure supporting <strong>LLM-powered applications</strong>, including embeddings, vector search, and <strong>RAG pipelines</strong></li><li>Develop systems for <strong>real-time decisioning</strong>, including pricing, personalization, and recommendation engines</li><li>Build and maintain <strong>experimentation platforms and A/B testing infrastructure</strong></li><li>Optimize data pipelines and ML workflows for <strong>performance and scalability</strong>, including GPU-based training environments</li><li>Collaborate with product, engineering, and data teams to operationalize machine learning models in production</li></ul><p><br></p>

<p><strong>Required Qualifications</strong></p><ul><li><strong>5+ years</strong> of experience in machine learning engineering, data engineering, or ML infrastructure</li><li>Proven experience building <strong>internal data and ML platforms used across multiple teams</strong></li><li>Experience implementing <strong>LLM infrastructure</strong> (embeddings, vector databases, vector search, RAG pipelines)</li><li>Experience developing <strong>real-time decisioning systems</strong> such as recommendations, pricing, or personalization engines</li><li>Experience building <strong>experimentation frameworks or A/B testing infrastructure</strong></li><li>Hands-on experience with <strong>deep learning workflows or GPU-based training systems</strong></li><li>Strong programming experience in <strong>Python and SQL</strong></li><li>Experience working with <strong>modern data platforms and cloud infrastructure</strong></li></ul><p><strong>Preferred Background</strong></p><ul><li>Experience in <strong>consumer technology, sports, marketplaces, or entertainment platforms</strong></li><li>Familiarity with <strong>large-scale data systems and distributed ML infrastructure</strong></li><li>Experience deploying and monitoring <strong>production ML systems</strong></li></ul><p><br></p>

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