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Yupp

Staff+ AI Engineer

Posted 14 Days Ago
Be an Early Applicant
In-Office
3 Locations
Expert/Leader
In-Office
3 Locations
Expert/Leader
The Staff AI Engineer will design and maintain AI applications, oversee the full ML lifecycle, collaborate with teams, and ensure model efficiency and scalability.
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About Yupp

We are a well-funded, rapidly growing, early-stage AI startup headquartered in Silicon Valley that is building a two-sided product -- one side meant for global consumers and the other side for AI builders and researchers. We work on the cutting edge of AI across the stack. Check out our product that was launched recently, and how it solves the foundational challenge of robust and trustworthy AI model evaluations. Here's more information about us.

Why Join Yupp?

Are you ready to have the ride of a lifetime together with some of the smartest and most seasoned colleagues? You’ll work on challenging, large-scale problems at the cutting edge of AI to build novel products that touch millions of users globally, in a massive and growing market opportunity.

Yupp’s founding team is highly experienced and comes from companies like Twitter, Google, Coinbase, Microsoft and Paypal. This team is one of the smartest, most fun, cracked top talent you will ever work with. Our work culture provides a high degree of autonomy, ownership and impact. It’s intense and isn’t for everyone. But if you want to build the future of AI alongside others who are at the top of their game and expect the same from you, there’s no better AI startup to be.

At Yupp, you will experience both the excitement of building for a large scale global user base as well as for the deeply technical audience of AI model builders and researchers. You’ll get immersed in and learn all about the latest and greatest AI models and agents. You’ll interact with AI builders and researchers from other AI labs all around the world.

We are a mostly in-person startup, but we are also flexible – you can usually work from home when you need to and come in and leave when you want to. Many employees work from home on average 1 day a week.

Responsibilities
  1. Stay up to date on emerging trends in GenAI and LLM advancements, identifying opportunities for application within the company.

  2. Design, build, and maintain LLM applications that meet high performance and reliability standards.

  3. Own the full ML lifecycle, including data analysis, preprocessing, model architecture, training, evaluation, and MLOps.

  4. Collaborate with product engineers, designers, and data scientists to develop cutting-edge AI solutions.

  5. Communicate complex technical concepts clearly to both AI experts and non-technical audiences.

  6. Troubleshoot, debug, and optimize AI models for scalability and efficiency.

  7. Write clean, maintainable, and well-documented production code.

Qualifications
  1. Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field (Ph.D. or equivalent experience is a plus).

  2. Minimum of 10 years of experience in machine learning, with proven success deploying AI models in real-world applications.

  3. Strong programming skills in Python, with familiarity in libraries such as PyTorch, TensorFlow, NumPy, and JAX.

  4. Deep understanding of machine learning algorithms, data structures, and model evaluation methodologies.

  5. Strong background in modern LLM architectures and applications, and experience in using GenAI approaches in an applied, production environment.

  6. Excellent communication and presentation skills, with the ability to clearly explain design decisions.

  7. Strong analytical and problem-solving skills, able to work independently and collaboratively in a fast-paced environment.

Preferred Qualifications
  1. Authored or co-authored research papers in reputable AI/ML conferences or impactful technical blog posts.

  2. Active participation in open-source AI/ML repositories, Kaggle competitions, or similar projects.

  3. Experience working in startup or small, fast-paced environments.

Top Skills

Jax
Numpy
Python
PyTorch
TensorFlow

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