AI Research Scientist

Hum; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Join a forward-thinking startup dedicated to creating positive impacts through AI and earth observation. As an AI Research Scientist, you will leverage your expertise in machine learning to design innovative models that contribute to nature conservation and carbon dioxide removal. This role offers the opportunity to work on groundbreaking projects, collaborate with a talented team, and influence the future of AI in environmental applications. If you are passionate about making a difference and have a strong background in generative AI, we invite you to apply and be part of this exciting journey.

Qualifications

• 5+ years of experience in machine learning research.
• Strong understanding of generative AI and deep learning.

Responsibilities

• Design and build cutting-edge AI models for earth observation.
• Prepare and publish technical papers in peer-reviewed conferences.

Skills

Machine Learning Research

Generative AI

Scientific Communication

Scripting (Python, Bash, PowerShell)

Education

PhD in Computer Science or Engineering

Tools

PyTorch

TensorFlow

Job description

Who are we?

Coastal Carbon is a seed-funded startup on a mission to create positive impact through earth observation and AI. Founded at the University of Waterloo by a team of PhDs and engineers, we’re backed by some of the best AI and climate tech investors like HF0, Inovia Capital and Propeller Ventures, angels like James Tamplin (cofounder Firebase) and Sid Gorham (cofounder OpenTable, Granular), and partners like Amazon AWS and the United Nations.

What do we do?

We’re building multimodal foundation models for the natural world. We believe there’s more to the world than the internet + more to intelligence than memorizing the internet. Our models are trained on satellite remote sensing and real world ground truth data, and are used by our customers in nature conservation, carbon dioxide removal, and government to protect and positively impact our increasingly changing world. Our ultimate goal is to build AGI of the natural world.

About the role

We are looking for an AI Research Scientist to join our team and contribute to designing and building cutting-edge models.

The role will involve:

• Research & Design:

  • Deep understanding of current machine learning research.

  • Proven track record of generating new ideas or enhancing existing ones in machine learning, evidenced by first-author publications or projects.

  • Contribute to research that uncovers the semantics of large datasets, with a focus on earth observation and remote sensing data.

  • Ability to independently manage and execute a research agenda, selecting impactful problems and conducting long-term projects autonomously.

• Implementation:

  • Developing high-level proof-of-concept (POC) models.

  • Experimenting with new state-of-the-art techniques to surpass existing models.

  • Plan and execute innovative research and development to push the boundaries of current technology.

• Writing and Publication:

  • Assisting in the preparation and writing of technical and scientific papers for publication.

  • Demonstrated strong scientific communication/presentation skills.

Requirements

• PhD degree in computer science, engineering, a related field, or equivalent experience.

• Proven track record of successful machine learning research projects

• 5+ years of experience in relevant jobs

• Strong scientific understanding of the field of generative AI

• Experience showing first-author publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL)

• Location wise, strong preference for in-person in San Francisco. We are an entirely in-person team, but are willing to consider remote for exceptional candidates.

Nice to have

• Proficiency in scripting languages such as Python, Bash, or PowerShell.

• Demonstrated experience with deep learning and transformer models.

• Familiarity with designing, training, and fine-tuning large models.

• Proficiency in frameworks like PyTorch or TensorFlow.

• Strong technical engineering skills.

• Previous experience in creating high-performance implementations of deep learning algorithms.

• Team player, willing to undertake various tasks to support the team.