Career Opportunity / 

Software Engineer - Deep Learning for Biodiversity Science

Yale University & Map of Life Rapid Assessments - XPRIZE 

Software Engineer - Deep Learning for Biodiversity Science 

The Yale Center for Biodiversity and Global Change is seeking an enthusiastic software engineer with a background in deep learning and a passion for applications of machine learning to environmental science and conservation. You will contribute to the training, testing, and deployment of deep learning models for species detection and identification in visual (camera trap, drone) and acoustic recordings.


The Yale Center for Biodiversity and Global Change and its flagship Map of Life (MOL) project are advancing new technologies for the rapid documentation of local biodiversity. Map of Life delivers research and information about the distribution and conservation of biodiversity in a changing world to science, policy, business, local communities, and educators. Map of Life Rapid Assessments takes the power of Map of Life to the local scale and combines with novel survey technologies to deliver relevant local biodiversity insights.  

Map of Life Rapid Assessments inventories local species communities with remotely operated visual and acoustic sensors in combination with expert knowledge and AI. Our subsequent analysis then combines AI with human-in-the loop approaches to identify species. Our approach and team have now been selected as one of the six finalist teams in the XPRIZE Rainforest competition

Within the processing pipeline, machine and deep learning play an important role and are used for selection and prioritization of recordings for further analysis. In this next phase we will scale up the development of new models and we are looking for a talented team member with experience in deep learning for computer vision or bioacoustics to assist with this effort.

Your primary task will consist of working with the MOL data science and machine learning staff to develop, assess, and refine models for species detection and identification in photos, videos, and acoustic recordings. Methodologies may include supervised fine-tuning, self-supervised pre-training, or active learning with expert input.

Position duration is a minimum of 6-12 months for 20-40 hours per week. Long-term employment opportunities may be available following the initial appointment. A combination of remote and in-person work can be accommodated. Position available to start immediately.

Your profile

Candidates should bring:

  • Excellent knowledge and experience in deep learning and software stacks (Python, PyTorch/TensorFlow/Jax).
  • A BSc. or higher in Computer Science, Data Science, Statistics, or in Ecology, Conservation, Remote Sensing or a similar field.

The following skills are optional assets:

  • Experience in multi-modal deep learning (visual, acoustic) and application of data science methods to real-world problems.
  • Familiarity with cloud storage and relational databases (PostgreSQL, etc.) and programmatic access to both.

Application Instructions

We are excited to receive your application! Please send the following documents to [email protected]:

  • Cover letter
  • CV or resume
  • Contact information for two referees

For more information and questions about the position or advertisement please contact Benjamin Kellenberger ([email protected]). To view our other open positions please visit

We strongly encourage members of underrepresented groups in the sciences to apply. Historical and ongoing social inequities rooted in racism, sexism, ableism, and other forms of discrimination result in the continued and widespread exclusion of marginalized groups from academic spaces. At our Center, we strive to support individuals from diverse backgrounds and to create a safe and inclusive community to counter these legacies of discrimination within the ecological and environmental sciences. We are actively committed to building a team and community where individuals representing a variety of paths to the sciences are brought together to foster a community of learning and collaboration. We hope that our commitments and actions create a more supportive and inspiring environment for individuals and contribute to a more inclusive and equitable future for our field.

Yale University offers a thriving and growing international community of young scholars in ecology, evolution and global change science in the Department of Ecology and Evolutionary Biology, the Yale Institute for Biospheric Studies, the Peabody Museum, and the School of the Environment. Yale University is located two hours north of New York City with many public transportation options to explore surrounding cities.