Factored AI Machine Learning & GenAI Residency
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.
Our Program:
The Factored AI Machine Learning & GenAI Residency is a full-time, paid professional residency designed for experienced engineers who want to operate at a higher level of responsibility, complexity, and impact. This residency is not a course or a traditional training program. It is a selective, execution-driven environment where engineers validate and elevate how they build and operate real Machine Learning and Generative AI systems in production.
Residents work within real constraints, alongside peers who meet the same engineering bar, on systems that matter.
Highlights
- A full-time, paid residency with clear professional expectations
- Work on real production systems, not academic exercises or toy projects
- Ownership of system-level decisions across architecture, performance, reliability, and cost
- Continuous technical evaluation through real execution, not exams
- Exposure to the standards used to build and operate AI systems for U.S. companies
This residency is designed to function as a professional validation layer for senior engineers.
Structure & Support
The residency operates as a structured professional track focused on execution.
- Residency Period: 12 to 16 weeks, depending on readiness and scope
- Time Commitment: Full-time (approximately 45 hours per week)
- Environment: Hands-on execution, technical reviews, system-level discussions
- Compensation: Paid, reflecting the professional nature of the residency
Residents are supported with access to infrastructure, peer feedback, and senior technical guidance aligned with Factored’s engineering standards.
Qualifications
We are looking for engineers who already have strong foundations and real production experience.
Required background:
- 4+ years of experience building and deploying Machine Learning systems in production
- Strong Python proficiency, writing production-grade code
- Solid understanding of Deep Learning fundamentals, including model architecture, optimization, and training dynamics
- Experience working with NLP and modern ML frameworks such as PyTorch, TensorFlow, or Hugging Face
- Backend experience building APIs with FastAPI or Flask
- Experience with containerization and cloud deployment (AWS, Azure, or GCP)
- Familiarity with production MLOps practices, including CI/CD, model versioning, monitoring, and infrastructure as code
- Strong written and spoken English, with the ability to communicate technical decisions clearly
- Must be based in LATAM
This residency is not designed for beginners or engineers without prior production exposure.
Program Logistics
- Start Date: February 16, 2026
- Program Type: Full-time, paid residency
- Focus: Execution-first, production-grade AI systems
- Duration: 12 to 16 weeks
Factored does not charge upfront fees to participate. Any contractual terms related to participation and long-term engagement are communicated transparently during the process.
Admission Process
The admission process is designed to evaluate real-world readiness and system-level thinking.
- Online Assessment: Evaluation of core technical foundations and problem-solving ability
- Talent Interview: Assessment of communication, clarity of thought, and professional alignment
- Technical Interview: Deep dive into prior production experience and decision-making
- System Design Interview: Evaluation of architecture thinking, trade-offs, and cultural fit
Admission is selective by design.
Our 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.
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