Research Engineer - Multimodal

Key Skills

Aartificial intelligence, Apache Beam, CUDA/GPU programming, Deep Learning, GPUs, JAX framework, Machine learning techniques, PyTorch, Spark Core, TensorFlow

Job Description

About us

Character’s mission is to give everyone on earth access to their own deeply personalized superintelligence that helps them live their best lives.

Achieving our mission will require solving ambitious technical challenges, including engineering, research, and design, and we are assembling a world-class team to do so. Our founding team includes AI pioneers from Google Brain and Meta Research whose research has led to major breakthroughs in natural language understanding and dialog applications such as Transformers and Google LaMDA.

Check out our beta to get a glimpse into the future.

About the role

We’re looking for scrappy and self-motivated people who have full-stack machine learning skills: collecting data, training state-of-the-art models, building evaluations, writing efficient inference algorithms, and iterating on user feedback.

In the day-to-day, you will be responsible for developing new AI capabilities end-to-end. This means you will need to wear a lot of hats across the full ML stack. You should be comfortable thinking about all parts of the problem, and ready to work on any and all components of it.

Responsibilities:

• Determining the type of training data we need, finding where we can collect it, and writing distributed data gathering pipelines to ingest data
• Developing new model architectures that push the state-of-the-art in terms of quality, scale, and inference speed
• Creating new evaluations that capture different aspects of generative outputs
• Writing fast inference algorithms to serve these models at scale
• Working with product teams to integrate feedback mechanisms into the product, which we use to improve the model

Requirements:

• Need at least 2+ years of industry experience working deep in the weeds on hard ML problems.
• Negative example: just stringing together a bunch of pre-existing components together. Need signal that this person can think critically about different parts of the pipline
• Have a deep understanding of the “whole stack” when it comes to designing, training, evaluating and deploying machine learning models, especially large language models.
• Collected a new giant dataset
• Published research papers
• Played a critical role in shipping a new ML product that required custom components
• Writing distributed ML infrastructure
• Have debugged and fixed hard-to-find bugs in ML models
• Have a track record of successfully owning projects from start to finish.
• Have experience with generative models for various modalities.
• Experience working with proven tools: ML frameworks (Tensorflow, PyTorch, Jax, …), data processing frameworks (Spark, Beam, …).

Character is an equal opportunity employer and does not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability or any other legally protected status. We value diversity and encourage applicants from a range of backgrounds to apply.