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Become a Machine Learning Engineer, Generative AI & LLMs Expert

Latin America

Factored was conceived in Palo Alto, California by Andrew Ng and a team of highly experienced AI researchers, educators, and engineers to help address the significant shortage of qualified AI & Machine-Learning engineers globally. ​We know that exceptional technical aptitude, intelligence, communication skills, and passion are equally distributed around the world, and we are very committed to testing, vetting, and nurturing the most talented engineers for our program and on behalf of our clients.

We are seeking a Machine Learning Engineer who is passionate about building state-of-the-art Generative AI solutions, particularly Large Language Models (LLMs) and Multi-Agent Systems. You will strengthen both your technical and soft skills through a combination of online learning, collaborative sessions, and hands-on practice. Throughout the program, you’ll take part in a combination of asynchronous learning (self-paced online content) and synchronous sessions led by our Training and Talent teams—where you’ll have the chance to share insights, discuss challenges, and get guidance along the way. At Factored, you will be rewarded with an amazing team that supports you, a rich culture, shared success, and the flexibility to work from the comfort of your home.

BOOSTING PROGRAM!

We are excited to launch a six-week Boosting Program, a full-time intensive experience designed to transform strong quantitative and coding skills into cutting-edge expertise. This program focuses on building advanced capabilities in areas such as exploring key LLM concepts, experimenting with frameworks, and understanding the components of modern GenAI systems, the next evolution in AI systems: Agentic Architectures. You’ll learn how to build multi-agent workflows and design intelligent systems capable of reasoning and action, as well as improve your knowledge and exposure to RAGs and LLMOps. 

As a Machine Learning Engineer (LLMs), you’ll design, implement, and optimize advanced NLP solutions to solve complex, real-world challenges across diverse domains. Our goal is to help you sharpen your LLM expertise, elevating you from an expert to a true master. You won’t just use the tools; you’ll understand their inner workings, the fundamentals behind them, and how to push their boundaries to the next level.


Functional Responsibilities:

  • Engage in a combination of asynchronous learning (self-paced online content) and synchronous sessions led by our Training and Talent teams, providing opportunities to share insights, discuss challenges, and receive expert guidance.
  • Lead End-to-End ML Development: Design, develop, and deploy advanced machine learning models, with a strong focus on Retrieval-Augmented Generation (RAG), LLMs, and Generative AI solutions.
  • Build Intelligent Systems: Create and implement intelligent systems that effectively integrate retrieval and generation techniques, significantly enhancing model performance and real-world usability.
  • Model Optimization & Deployment: Implement and optimize complex NLP and deep learning models using frameworks like PyTorch/TensorFlow for robust, scalable production environments.
  • Drive Innovation: Explore and apply cutting-edge methodologies, such as advanced prompt engineering, model fine-tuning, and AI agent automation, to push the boundaries of our solutions.
  • Ensure Scalability: Work with cloud computing platforms (AWS, GCP) or equivalent on-premise solutions to guarantee reliable and scalable deployment of all AI systems.
  • Cross-Functional Collaboration: Work closely with software engineers, data scientists, and product teams to seamlessly integrate AI solutions into real-world applications.
  • Effective Communication: Clearly and effectively communicate complex engineering challenges and innovative solutions to both fellow engineers and business partner teams.

Qualifications:

  • Education: Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Experience: 5+ years of hands-on experience in developing and deploying machine learning models, with 2+ years of direct experience working with production NLP and deep learning models.
  • Excellent English communication skills.
  • Technical Stack: Strong Python skills and adherence to coding best practices.
  • Framework Proficiency: Deep proficiency with PyTorch/TensorFlow for deep learning and NLP applications. 
  • Generative AI Exposure:
    • Expertise in Retrieval-Augmented Generation (RAG) and other techniques to enhance AI model capabilities.
    • Hands-on experience with LLMs and Generative AI frameworks (e.g., Hugging Face, OpenAI API, LangChain).
    • Strong understanding of prompting techniques, including the trade-offs between prompt engineering and fine-tuning.
    • Proficiency in developing AI agents and automation workflows.
  • Infrastructure: Experience with cloud computing (AWS, GCP) or equivalent on-premise platforms for model deployment.
  • Communication: Excellent communication skills, with the ability to articulate complex engineering concepts clearly and effectively to diverse audiences.
At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you.  
 
We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth are available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high-performing fast-growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts. 
 
In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission.  When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.

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