Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field.
5+ years of hands-on experience developing and deploying machine learning models in production environments.
4+ years of experience with production NLP and deep learning models using frameworks like PyTorch and TensorFlow.
At least 1+ year of experience with Retrieval-Augmented Generation (RAG) and other advanced techniques to optimize model performance.
Proven experience writing production-level code, with strong proficiency in Python.
Expertise in working with large language models (LLMs) such as GPT, Gemini, and Claude, along with proficiency in LLM frameworks like LangChain.
Strong understanding of prompting techniques, and the trade-offs between prompting and fine-tuning.
Experience with cloud platforms such as AWS or GCP (AWS preferred), or equivalent on-premise platforms.
Benefits
Ownership through equity participation.Annual company retreat.Education bonus for continuous learning.Company-wide winter break.Paid time off.Optional in-person events and meetups.Tailored career roadmaps.High-performance culture.Remote work optionsEquity / stock optionsPerformance bonus
Additional Information
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.
We are seeking a skilled Senior Machine Learning Engineer to join our team, with a specialized focus on Retrieval-Augmented Generation (RAG) models. The ideal candidate will have experience in designing, developing, and deploying advanced machine learning models that integrate retrieval and generation capabilities to create powerful AI-driven applications.
Functional Responsibilities:
Design, develop, and optimize Retrieval-Augmented Generation (RAG) models that integrate retrieval-based and generation-based approaches to solve complex, real-world problems for our high-profile clients.
Improve the performance of RAG models through cutting-edge algorithms, innovative techniques, and model fine-tuning.
Collaborate with client Data and Engineering teams to establish and build robust machine learning infrastructure to meet project goals.
Work closely with leadership teams from our clients to identify and leverage AI/ML opportunities that can provide transformative solutions.
Fine-tune and adapt large language models (LLMs) for specific tasks and domains within the RAG framework.
Partner with cross-functional client teams to deploy RAG models into production environments, ensuring seamless integration and long-term success.
Apply advanced machine learning techniques, including LLMs, to develop effective AI solutions tailored to client needs.
Write clean, maintainable, and scalable code, ensuring all development is well-documented and testable.
Prioritize user experience and customer needs in all product development efforts.
Design and develop frameworks for GenAI products, such as search interfaces, chatbots, and summarization tools.
Build and implement machine learning models and algorithms that directly contribute to client growth and success through innovative, AI-driven solutions.
Provide technical leadership in identifying and evaluating AI/ML opportunities that empower clients to deliver exceptional solutions.
Factored · Latin America