About The Role: How do AI teams detect edge cases faster? What’s the best way for AI leaders to measure annotation pipeline performance? As our Technical Content Lead, you'll translate challenges you've likely faced yourself - dataset quality issues, annotation workflows, model performance issues - into content that resonates with AI and ML teams. You'll bring hands-on experience from data ops, ML engineering, or data infrastructure. You understand dataset quality issues, annotation workflows, and model performance issues. That technical foundation is what enables you to create content that ...

About The Role: We're looking for a Developer Advocate AI/ML to become the technical voice of Encord in the AI/ML developer community and leadership ecosystem. You'll create compelling technical content, speak at industry events, and build authentic relationships with practitioners building production AI systems as well as technical leaders shaping AI strategy. You'll represent Encord at major conferences and technical meetups, engaging with everyone from engineers to Directors of AI/ML, VPs of Engineering, and CTOs. This role combines technical education with executive-level thought leaders...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building AI. AI...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building AI. AI...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is actually not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is actually not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Us At Encord , we’re building the AI infrastructure of the future. The biggest challenge AI companies face today is actually not half as glamorous as the outside world may think: it’s all about data quality. In fact, the success of any AI application today relies on the quality of a model’s training data and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of ...

About Us At Encord, we're building the AI infrastructure of the future. The biggest challenge AI companies face today is not half as glamorous as the outside world may think: it's all about data quality. In fact, the success of any AI application today relies on the quality of a model's training data — and for 95% of teams, this essential step is both the most costly, and the most time-consuming, in getting their product to market. As ex-computer scientists, physicists, and quants, we felt first-hand how the lack of tools to prepare quality training data was impeding the progress of building...

About Encord At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We’re here to change that. As former computer scientists, physicists, and quants, we’ve experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet—wh...

About Encord At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We’re here to change that. As former computer scientists, physicists, and quants, we’ve experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet—wh...

About Encord At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We’re here to change that. As former computer scientists, physicists, and quants, we’ve experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet—wh...

About Encord At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We’re here to change that. As former computer scientists, physicists, and quants, we’ve experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet—wh...

About Encord At Encord, we're building the AI infrastructure of the future. One of the biggest challenges AI companies face today is data quality. The success of any AI application relies heavily on the quality of its training data, yet for most teams, this crucial step is both the most costly and time-consuming. We’re here to change that. As former computer scientists, physicists, and quants, we’ve experienced firsthand how a lack of tools to prepare quality training data impedes progress in building AI. We believe AI is at a stage similar to the early days of computing or the internet—wh...