Data Scientist - LLM

We’re looking for a talented and intensely curious LLM specialist and deep learning modeler that is nimble and focused with a startup mentality: You want your models and code to ship and improve the lives of real customers, not rot in a research department. You’ll be fine-tuning and serving various models, but you’ll also obsess over learnings in the industry and apply them in your daily work. Like for all of us, the outcome matters more to you than how we get there. You get a kick out of serving tools that improve and accelerate the workflows of the top YouTube creators in the world! If that all sounds like you, keep on reading.

What You’ll Do

• You’ll fine-tune and serve LLMs and LLM-based pipelines to help build best-in-class workflow tools for the world’s top YouTube creators, and you’ll ship updates and new features on a weekly basis
• You’ll be part of a small but mighty and highly motivated team (~15 people strong) that operates like a startup within a startup–with all the chaos that comes with that–but also real camaraderie, diverse backgrounds, skills and opinions and plenty of fun.
• You’ll learn and grow every day - from the industry, your peers and most importantly, your customer zero - the creators!

Responsibilities

• Fine-tune pre-trained language models for generative AI applications.
• Apply, discover and research techniques to optimize existing LLM training and serving, as well as improving the model quality.
• Develop and deploy the LLMs for a variety of content generation tasks.
• Share your discoveries, learnings and results with other modelers in the company working on related projects.
• Continuously research and stay up-to-date with recent advancements in NLP and large language models, applying novel techniques and methodologies to improve our models.
• Read all the newsletters and obsess over new industry learnings, startups utilizing LLMs in novel ways, and other ways the real world is utilizing LLMs.
• Conduct experiments and benchmarking to assess the performance of various model architectures and optimize hyperparameters.
• Troubleshoot and resolve any issues arising during model training and deployment.
• Work with product teams to ensure smooth product delivery with high standards, prioritize short-term returns and long-term growth.

Who You Are

• PhD in Data Science related field (Machine Learning, Computer Science, Statistics, etc...)
• Hands-on experience in developing models, in optimizing model training and tuning and in deploying Large Language Models such as GPT, LLaMA, BERT, or Transformer-based architectures with strong knowledge in tokenization and embeddings.
• Experience in developing deep learning models as a Data Scientist and experience in building products backed up ML /AI
• Experience with transfer learning, meta learning and predictive modeling.
• Expertise in visualizing and manipulating big datasets.
• Strong analytical and problem-solving skills and 
• Intensely curious to learn how AGI is evolving day in and day out.
• Excited about creators 
• Excellent oral and written communication skills.
• Good knowledge in other deep learning models such as CNN, RNN.
• Take a creative and strategic approach to solve hard problems. Simplify the complex. Bring in fresh ideas from new places.

Why Spotter

• Medical insurance covered up to 100%
• Dental & vision insurance
• 401(k) matching
• Stock options
• Complimentary gym access
• Autonomy and upward mobility
• Diverse, equitable, and inclusive culture, where your voice matters.

In compliance with local law, we are disclosing the compensation, or a range thereof, for roles that will be performed in Los Angeles. Actual salaries will vary and may be above or below the range based on various factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. A reasonable estimate of the current pay range is: $150K-$250K salary per year. The range listed is just one component of Spotter’s total compensation package for employees. Other rewards may include an annual discretionary bonus and equity.