Sequen AI

The first Behavior Design Engine for the enterprise. Sequen isn’t retrofitted AI search or recommendations. It rethinks relevance from first principles. Sequen introduces the first foundational Large Event Model (LEM), trained on billions of user event sequences and built natively on a reinforcement learning infrastructure. LEMs are specialized neural networks that predict the next user event—just as LLMs predict the next word. Sequen’s LEMs are pre-trained on billions of user-site interactions and fine-tuned to optimize for the outcomes you care about. No more fixed pipelines with fragmented infrastructure. Sequen replaces them with a single endpoint that adaptively handles all phases of personalization via LEMs and memory models—all through a sub-25ms API.

Senior Research Engineer – Search & Recommendation Ranking

Full TimeRemoteTeam 8

Location

United States

Posted

9 days ago

Salary

$280K - $350K / year

Bachelor Degree9 yrs expEnglishAirflowAWSDeep LearningGCPKubernetesPy TorchSparkTerraform

Job Description

About Us Sequen AI is leading the charge for building frontier ranking models for search and recommendations. Sequen AI's technology specializes in designing end-user behavior for large consumer enterprises. The Role We’re looking for a Senior Research Engineer with expertise in search and recommendation modeling to help us design, develop, and scale innovative ranking, embedding and retrieval models that power our personalized discovery platform. In this role, you’ll have the opportunity to work on impactful projects, from enhancing recommendation ranking systems to building search retrieval models, all while contributing to the underlying data pipelines and infrastructure. This is an ideal role for someone eager to grow their skills, take ownership of complex systems, and be part of an agile, fast-paced environment. What You'll Do Develop & Optimize Ranking Models : Build, train, and deploy advanced search and recommendation models using Deep Learning techniques. Data Engineering : Design and implement data pipelines to process large-scale datasets, ensuring models are fed with high-quality, reliable data. Infrastructure : Work with tools like Kubernetes, Airflow, and AWS to manage scalable model deployment and experimentation environments. What We’re Looking For Experience : 5+ years of experience as an ML Engineer or similar role, with a focus on deep learning for search, recommendation, or related applications. Technical Expertise : Proficient in PyTorch, Deep Learning, and Spark, with a strong foundation in machine learning theory and algorithms. Data Engineering Skills : Hands-on experience with data pipelines and processing large-scale datasets. You'll design and optimize data pipelines using tools like Spark, Airflow, and dbt across GCP and AWS. Infrastructure Knowledge : Some familiarity with tools such as Kubernetes, Airflow, Terraform and cloud platforms like AWS for deployment and scalability. Problem Solver : Strong analytical and critical thinking skills, with a passion for tackling open-ended challenges. What We Offer A collaborative and innovative work environment at the forefront of ML and AI. Opportunities to make a direct impact on product and technology direction. Annual Salary : $280,000—$350,000 USD (based on experience) + Equity Health insurance, unlimited time off, awesome team If you’re excited about building next-generation search and recommendation systems and growing your expertise in a dynamic startup, we’d love to hear from you!

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