Deep Learning Research Engineer
Required skills
+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
Preferred skills
Industry experience with efficient inference deployments (cloud or edge), Experience with Deep Reinforcement Learning
Technologies
PyTorch, TensorFlow, Keras, JAX, Kubernetes, Snowflake, Dataflow, Streamlit, GCP
Responsibilities
Use and improve multimodal LLMs to achieve new functionality for customers, optimize deployments (cloud and edge), train and design more accurate models, enable new and more complex AI applications on low-cost and low-power hardware, improve data pipeline, model architectures and training software, use Kubernetes cluster to deploy PyTorch and TensorFlow training jobs, use Snowflake and Dataflow to build datasets, use tools like Streamlit to prototype new demos, use lots of GPUs on GCP for training new models and auto-labeling data
Seniority
Not specified
Domain
Computer vision, AI, machine learning, embedded systems, multimodal LLMs