Fully remote | Complete engagement job Founded in Palo Alto by Dr. 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 Forward Deployed ML/AI Engineer , you will bridge the gap between cutting-edge AI research and robust, production-grade applications. You will be responsible for the end-to-end lifecycle of intelligent systems, from data ingestion and model training to deployment. This role requires deep technical proficiency in training and tuning classical machine learning models (such as gradient-boosted trees, random forests, and regression suites) alongside modern Generative AI architectures, including Large Language Models (LLMs), retrieval-augmented generation (RAG) pipelines, and agentic workflows.

You will design scalable APIs, optimize model inference latency, and architect full-stack infrastructure to ensure AI capabilities are seamlessly delivered to end-users. You are both a technical builder and a strategic business partner, embedded within customer environments to deliver measurable AI outcomes. You will bridge the gap between cutting-edge AI research and robust, production-grade applications while serving as a translator between technical capabilities and business objectives.

Your mission goes beyond model development—you will own the end-to-end delivery of intelligent systems that directly impact customer business metrics. You will design scalable APIs, optimize model inference, architect infrastructure, AND guide executive stakeholders through complex technical decisions. You will identify high-impact opportunities where machine learning can drive efficiency or unlock new product capabilities, working collaboratively across customer organizations (technical, product, operations, and business teams) to ensure solutions deliver real, measurable business value.

This role requires exceptional ability to navigate ambiguity, build trust with diverse stakeholders, and operate effectively in fast-paced, cross-functional customer environments where you'll often be the most technical person in the room—yet must communicate that expertise clearly to non-technical decision-makers.

Responsibilities

: Cross-Functional Stakeholder Leadership: Translate complex business

Requirements

into technical AI specifications in collaboration with product, operations, and business teams. Serve as the technical authority on AI/ML topics while remaining approachable to non-technical stakeholders. Manage expectations, communicate risks transparently, and maintain stakeholder confidence through complex projects.

Lead alignment discussions when technical constraints conflict with business priorities. Coordinate with customer teams to ensure end-to-end delivery. Business Problem Definition Solution Architecture: Partner with customer leadership to clearly define business problems, success metrics, and constraints.

with explicit trade-off analysis. Present multiple solution approaches with pros/cons framed in business terms (time, cost, risk, user impact). Validate that proposed technical solutions will actually solve the stated business problem.

End-to-End AI Application Development Strategic Delivery: Design, build, and maintain full-stack applications integrating classical ML models and Generative AI components. Own delivery of AI applications from discovery through production deployment and ongoing optimization.