Responsibilities
- Leverage and enhance multimodal large language models to deliver novel features and optimize performance across cloud and edge environments.
- Design and train higher-accuracy neural networks that enable advanced AI capabilities on cost-effective, low-power devices.
- Enhance data processing workflows, model designs, and training infrastructure for improved efficiency and scalability.
- Deploy deep learning training tasks using PyTorch and TensorFlow on Kubernetes clusters.
- Construct training datasets using Snowflake and Google Cloud Dataflow.
- Develop interactive prototypes and demonstrations using tools such as Streamlit.
- Utilize extensive GPU resources on Google Cloud Platform for model training and automated data labeling.
Requirements
- Minimum of five years of professional software development experience with strong Python skills.
- Proficiency in deep learning frameworks including PyTorch, TensorFlow, Keras, or JAX.
- Proven background in computer vision and multimodal large language models.
- Experience training neural networks that were successfully deployed in production environments.
Nice to Have
- Industry experience deploying AI models efficiently in cloud or edge settings.
- Background in Deep Reinforcement Learning applications.
Work Arrangement
Hybrid — London, Amsterdam
Other
- Flexible working hours.
- Mandatory in-person collaboration at offices for at least two fixed days each week.
- Relocation support and visa sponsorship available.
- Freedom to select personal work laptop and equipment.
- 25 days of paid vacation plus public holidays.
- Opportunity to attend leading AI research conferences such as NeurIPS, ICML, and CVPR.
Yes
