We are looking for a Senior Deep Learning Research Engineer to help develop state-of-the-art AI products for embedded devices. You will work on improving training algorithms, training and integrating multimodal LLMs, building data pipelines, designing new model architectures, and developing clever algorithms. You will help build new AI features shipped to millions of camera devices.
What you will be doing:
- Combine Tiny AI with multimodal LLMs to enable advanced AI features for customers and optimize deployments (cloud and edge)
- Train and design more accurate models while enabling new and complex AI applications on low-cost and low-power hardware
- Improve data pipeline, model architectures and training software using novel approaches and clever hacks
- Use Kubernetes cluster to deploy PyTorch and TensorFlow training jobs, Snowflake and Dataflow to build datasets, Streamlit for prototyping, and GPUs on GCP for training models and auto-labeling data
Requirements:
- +5 years of professional software engineering experience with proficiency in Python
- Comfortable with frameworks such as PyTorch, TensorFlow, Keras, or JAX
- Strong experience with computer vision and multimodal LLMs
- Trained neural networks that moved into production
Nice to have:
- Industry experience with efficient inference deployments (cloud or edge)
- Experience with Deep Reinforcement Learning