Overview
Jua's mission is to create artificial general intelligence (AGI). Our product uses a foundational Earth systems model to predict atmospheric events. It’s more accurate, faster, and updates more frequently than current weather models, making it valuable for traders in weather-dependent power markets. These benefits are crucial during extreme weather events like hurricanes and cyclones. As we scale the model, more applications will become possible, including wildfire, flood, and vegetation prediction.
By joining our talented multidisciplinary team, you'll help shape our culture of ambition, transparent communication, and rapid iteration. We offer exciting challenges, creative freedom, fair pay, and generous stock options.
What we are looking for
As a Senior AI Researcher, you will develop and train state-of-the-art foundational earth systems models. As part of our fast-moving model research team, you will be working on developing and improving our deep learning-based algorithms and have great creative freedom and influence. Based on the latest publications, you will test and implement state-of-the-art research and, together with the team, build robust and sustainable machine learning pipelines for live operation.
Responsibilities and tasks
- Researching, implementing, and productionizing machine learning models for renewable power forecasting using satellite imagery, and other multi-modal data.
- Designing and training models on our GPU cluster with an emphasis on terabyte-scale environmental datasets.
- Creating novel algorithms to address challenges in climate modeling, from ideation and prototyping to live deployment.
Need to have
- Expertise in Python with the ability to quickly learn new programming languages as needed.
- Proficient in machine learning frameworks (e.g., PyTorch, TensorFlow, Keras, FLAX, TFX) and able to stay up to date with emerging tools and frameworks.
- Strong grasp of machine learning optimization techniques, including gradient clipping, mixed precision training, and layer parallelism
- Extensive knowledge of transformer architectures (e.g., GPT, Bart, Swin Transformer)
- Familiarity with advanced techniques such as diffusion models or graph neural networks and their relevance
- Experience with distributed training and inference architectures, including frameworks like Huggingface Accelerate and Microsoft DeepSpeed.
- Strong understanding of high-performance computing (HPC) and its role in accelerating machine learning workflows.
- Proven ability to work with terabyte-scale datasets, particularly those related to climate and geospatial data.
- General distributed systems knowledge and familiarity with public cloud offerings for ML workflows (e.g., GCP, AWS).
- Experience with tools like Git, Docker, Xarray, and Zarr.
- Demonstrated ability to independently solve complex problems with creativity and precision.
- Collaborative mindset with experience working in interdisciplinary teams.
- Awareness of the real-world, customer-facing impact of machine learning solutions, particularly in environmental applications.
- Background in GIS-based data, such as satellite imagery, radar data, or radiosondes.
Nice-to-have
- Experience with experiment tracking tools (e.g., WandB, MLflow).
- Hands-on experience running machine learning workloads in production environments.
- Contributions to open-source projects or the broader climate-focused machine learning community.
At Jua, we foster a performance culture and value people who embody our beliefs of service and adventure. We prioritize agility, operating at the highest clock speed to adapt quickly to change. We innovate on behalf of our users and leverage data supremacy to maintain our competitive edge. Through clear communication and fact-based decision-making, we ensure alignment in our pursuit of excellence. With these principles, we aim to create a customer-focused, value-centric organization that sets new standards in the industry. We value the unique perspectives that each individual brings to the table and believe that embracing diverse backgrounds and experiences enriches our collective journey towards growth and success.