Fully remote | Complete engagement job

Founded in Palo Alto by Dr. Andrew Ng and Israel Niezen, Factored helps U.S. companies build and scale world-class AI, ML, and Data teams, powered by the top 1% of LATAM talent, with a defining purpose: To empower brilliant humans, unleash their potential, and amplify their impact in the world.

At Factored, you’ll be part of a community that values learning, ownership, and authenticity, where your growth is personal and your ideas matter. We’re transparent, curious, and collaborative. We strive for excellence, celebrate diversity, encourage curiosity, and build an environment where you can truly thrive.

As a Machine Learning Engineer specializing in Recommender Systems, you will design, build, and optimize large-scale recommendation architectures that power personalized user experiences for enterprise environments. You’ll work across candidate generation, deep learning ranking models, and high-throughput real-time systems, owning recommendation pipelines end-to-end from experimentation to production deployment.

Functional Responsibilities:





• Design and implement multi-stage recommendation pipelines, including Candidate Generation (Retrieval), Ranking, and Re-ranking/Filtering stages.

• Develop and fine-tune machine learning and deep learning models for personalized recommendations using techniques such as Collaborative Filtering, Matrix Factorization, Two-Tower Networks, and Deep Learning (e.g., Deep & Cross Networks).

• Build and optimize two-stage retrieval architectures using Approximate Nearest Neighbors (ANN) vector search engines (e.g., Faiss, Pinecone, Milvus).

• Implement real-time scoring and inference pipelines using feature stores (e.g., Feast, Hopsworks) and scalable serving frameworks (e.g., Triton, TorchServe, Ray Serve).

• Establish A/B testing frameworks, offline evaluation metrics (NDCG, MAP, Recall@K), and real-time monitoring for model performance and business metrics.

• Optimize recommendation syst

📌 Senior Machine Learning Engineer (Modena)
🏢 Factored
📍 Modena