Advance Accelerator Program Machine Learning & GenAI
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:
Are you ready to accelerate your career and position yourself at the forefront of AI innovation? The Advanced Accelerator Training Program at Factored is a high-impact initiative explicitly designed for candidates looking to master cutting-edge technologies and transition into high-level roles within our organization.
Highlights ✨ :
- This isn't just a theoretical course—it is a rigorous, full-time commitment that bridges the gap between foundational skills and elite professional performance.
- You will move beyond theory by working on capstone projects based on real-world problems, literature reviews, and more.
- Gain invaluable insights through regular feedback sessions and lessons from industry experts focusing on both technical (hard) and professional (soft) skills.
- Upon successful completion, you will be prepared to work with our top-tier clients on technically demanding, high-impact AI projects.
🛠️ Structure & Support:
We provide the tools and environment you need to succeed from day one:
- Duration: Between 12 and up to 16 weeks, depending on your specific training needs.
- Full-Time Commitment and exclusivity: Expect to dedicate approximately 45 hours per week to the program.
- Note: A permanence clause applies. If you decide to leave Factored before completing two years, you must reimburse Factored for training expenses.
Qualifications:
- Minimum 4+ years in the Machine Learning field with a proven track record of implementing ML solutions in production.
- Python Development: Proficiency in writing production-grade Python code.
- Deep Learning Fundamentals: Strong grasp of model architecture (Layers, Weights, Biases, Activation Functions), Forward Propagation, Loss Functions, and the optimization loop (Backpropagation, Gradient Descent, and Learning Rates).
- NLP & Frameworks: Solid understanding of Natural Language Processing (NLP) with experience using PyTorch, TensorFlow, or Hugging Face to implement and fine-tune pre-trained models.
- Backend & API Development: Experience building APIs using FastAPI or Flask.
- Deployment & Cloud: Hands-on experience with containerization (Docker) and deploying ML models to cloud infrastructure (AWS, Azure, or GCP).
- MLOps: Familiarity with the ML lifecycle: CI/CD pipelines (GitHub Actions/GitLab CI), Model Versioning and Tracking (MLflow, Weights & Biases), Model Monitoring, and Infrastructure as Code (IaC).
- Excellent written and spoken English. You must be able to lead in-depth technical discussions with engineers while effectively communicating value to business stakeholders.
Program Logistics:
- Initial Start date: February 16, 2026
- Type of program: Full-time.
- Methodology: Mix of classroom and online content with extended discussions and assignments, literature review and paper implementation, capstone projects based on real-world problems and mentorship on soft-skills development.
- Duration: Between 12 to 16 weeks.
- Factored will pay a monthly stipend to all program participants to cover living expenses during the accelerator program.
- Factored does not charge any upfront fees to enroll and participate in the program. However, participants will need to sign a loan agreement for an amount equal to the cost of their participation. This loan will be fully repaid and cancelled after 2 years of full-time employment with Factored.
Admission Process:
- Online assessment: Applicants will receive an online assessment and will have 2 weeks to complete it. To prepare for the online assessment, you should: Refresh your Linear Algebra and Calculus knowledge, brush up on your Machine Learning and Deep Learning fundamental concepts. (bias and variance trade-off, common metrics, well-known models, well-known architectures, etc.) and practice basic Python (data structures and OOP) and Algorithmic Coding (e.g., solving LeetCode problems).
- Talent interview: Applicants who successfully pass the assessment will meet with the recruitment team for an interview to assess communication skills and technical concepts.
- Tech interview: Applicants will discuss their experience, exploring their practical and conceptual understanding of the tools and skills used in past projects. Scenarios will be proposed, and applicants will explain how they would approach and solve them.
- System design and cultural fit interview: Applicants will have an interview with one member of our team to determine alignment with the company's values, mission, and overall culture as well as their system design proficiency.
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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