Machine Learning Software Engineer (Remote)
*No Visa Sponsorship is available for this position.
About the Cornell Lab of Ornithology
The Cornell Lab of Ornithology is a tech-centered conservation organization with a mission to advance the understanding and protection of birds and biodiversity. By engaging millions of people across the globe who watch birds, producing scientific and technical resources, and partnering across governments, non-profits, and industry we are working to solve big environmental challenges. We rely on a small, dedicated team of engineers to curate more one than billion bird sightings and take creative approaches to building apps that help communities in all corners of the globe connect to birds and monitor bird populations. The Lab is in an incredible growth phase and navigating exciting challenges to scale our data-driven tools and services for conservation communities in all corners of the globe. eBird collaborates with hundreds of regional organizations in more than 80 countries who are using eBird and Merlin as a platform to advance their conservation goals.
The Opportunity
The Cornell Lab of Ornithology is seeking a creative, mission-driven Machine Learning Software Engineer to join the team that develops machine learning models incorporated into Merlin Bird ID, a mobile app that helps millions of people worldwide identify birds using automated detection and classification of birds in images, audio, and video. This role will join a team that shares the mission of connecting people to nature and conservation through birds. As part of a team of software engineers, content creators, machine learning researchers, and conservation scientists this role will be critical to integrate machine learning models into products for a global community of birders, researchers, and conservation practitioners.
This role will join an engineering team to design, implement, and maintain complex applications and datasets for training Merlin’s machine learning models and integrating models into apps and websites (in both online and offline contexts). This position will work at the intersection of machine learning research, global community participation in data collection, and production software systems, to deliver innovative public-facing software designed to engage people in birds and support conservation decision-making.
The Machine Learning Software Engineer will be expected to: 1) manage software engineering projects with multiple, concurrent development efforts, interact with both internal and external collaborators and architect application solutions, 2) serve as a primary technical liaison between internal engineering teams, supporting coordination and integration of application infrastructure to meet strategic objectives, 3) develop production applications, and 4) participate actively in the design and evolution of CLO technical systems, including the integration of machine learning research into production systems.
The Cornell Lab of Ornithology is an inclusive community, and we recognize that diverse, inclusive communities create more innovative and impactful work to address global challenges and benefit humanity and nature. The Cornell Lab is committed to fostering a healthy workplace that values diverse perspectives and backgrounds as well as supporting growth and advancement opportunities. The Lab welcomes staff who are still learning in their careers and who are motivated to take on new challenges.
What We Need
Required Qualifications:
If you have all those things, great! We have a few more things that we would prefer you to have, but it’s ok if you don’t.
Preferred Qualifications:
Application Information:
What We Offer
Rewards and Benefits
University Job Title:
Software Engineer IIIJob Family:
Information TechnologyLevel:
FPay Rate Type:
SalaryPay Range:
$95,071.00 - $110,487.00Remote Option Availability:
RemoteCompany:
Contract CollegeContact Name:
Maria AvilaJob Titles and Pay Ranges:
Non-Union Positions
Noted pay ranges reflect the potential pay opportunity for each job profile. The hiring rate of pay for the successful candidate will be determined considering the following criteria:
Prior relevant work or industry experience
Education level to the extent education is relevant to the position
Unique applicable skills
Academic Discipline
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Union Positions
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