Essential AI’s mission is to deepen the partnership between humans and computers, unlocking collaborative capabilities that far exceed what could be achieved today. We believe that building delightful end-user experiences requires innovating across the stack - from the UX all the way down to models that achieve the best user value per FLOP.
We believe that a small, focused team of motivated individuals can create outsized breakthroughs. We are building a world-class multi-disciplinary team who are excited to solve hard real-world AI problems. We are well-capitalized and supported by March Capital and Thrive Capital, with participation from AMD, Franklin Venture Partners, Google, KB Investment, NVIDIA.
The Data Annotation Lead will be responsible for curating mission critical annotated data for Essential’s machine learning models. You will work closely with cross-functional stakeholders to ensure collection of high-quality annotated data that drives the improvements in capabilities and performance of our models. This is a critical role that requires strong analytical skills, an eye for detail, and the ability to work efficiently and accurately.
Strategically partner with cross-functional stakeholders to understand end user objectives and requirements, and translate that into specifications for data annotation.
Layout a roadmap for annotation timelines, including feedback on what’s realistic and what’s aspirational.
Develop an annotation program to meet our capability requirements, including but not limited to clear instructions to a team of annotators, and identify where the gaps in the instructions may be; and perform quality checks on annotated data to ensure accuracy and consistency, making necessary corrections and improvements.
Meet deadlines and productivity targets while maintaining high accuracy rates.
Identify opportunities for process improvement and automation in data annotation workflows to increase productivity and quality.
Experience in data annotation or related roles, with a strong understanding of annotation techniques and best practices.
Familiarity with annotation tools / software. Bonus if you have built and design custom annotation tools.
Strong analytical and problem-solving skills with an eye for detail.
Strong communication and collaboration skills, with the ability to work effectively in a team environment.
Experience with text (structured and unstructured), image, audio, and/or video data annotation.
Knowledge of machine learning concepts and workflows is desirable but not required.
Deeply wants to understand the task, capabilities of the model, and success criteria of the task, partnering closely with Applied ML team to understand end user needs.
Should be able to take a higher level description of the dataset and convert that into specific requirements. For example, connecting the task requirements to iterate on the annotator interface and interaction mechanism.
Previous experience building or leading a data annotation team.
We encourage you to apply for this position even if you don’t check all of the above requirements but want to spend time pushing on these techniques.
We are based in-person in SF. We offer relocation assistance to new employees.