About us Encord is building the AI infrastructure of the future. Today, the biggest bottleneck in AI isn't algorithms—it's data quality. For most teams, preparing high-quality training data is the most time-consuming and expensive part of bringing AI products to market. Founded by former computer scientists, physicists, and quants, Encord exists to fix this. Just as early computing needed better tools to unlock its potential, modern AI needs better infrastructure to scale. We're building those tools. We're a fast-growing team of 100+ working at the cutting edge of computer vision and dee...

About us At Encord, we're building the AI infrastructure of the future by solving one of the least glamorous, but most critical, problems in AI: data quality. For the vast majority of teams, preparing high-quality training data is the most costly and time-consuming part of bringing AI products to market, and it ultimately determines whether models succeed or fail. As former computer scientists, physicists, and quants, we experienced this pain firsthand. AI today feels like the early days of the internet — huge potential, but immature tooling holding real progress back. That gap is why we s...

We’re excited to be meeting students and graduates from Harvard and MIT and to share more about Encord and the problems we’re working on. This application is an open expression of interest for candidates we meet (or connect with) through the Harvard & MIT career fairs who are interested in exploring opportunities at Encord — now or in the near future. At Encord, we hire across engineering, machine learning, forward-deployed roles, and technical customer-facing teams. While you may not see a role that’s a perfect match today, we often shape roles around exceptional people as we grow. How th...

Don't see a role that fits your profile? Reach out anyway! 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 stag...

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 by solving one of the least glamorous, but most critical, problems in AI: data quality. For the vast majority of teams, preparing high-quality training data is the most costly and time-consuming part of bringing AI products to market, and it ultimately determines whether models succeed or fail. As former computer scientists, physicists, and quants, we experienced this pain firsthand. AI today feels like the early days of the internet — huge potential, but immature tooling holding real progress back. That gap is why we s...

About us At Encord, we’re building the AI infrastructure of the future by solving one of the least glamorous, but most critical, problems in AI: data quality. For the vast majority of teams, preparing high-quality training data is the most costly and time-consuming part of bringing AI products to market, and it ultimately determines whether models succeed or fail. As former computer scientists, physicists, and quants, we experienced this pain firsthand. AI today feels like the early days of the internet — huge potential, but immature tooling holding real progress back. That gap is why we s...

About us At Encord, we’re building the AI infrastructure of the future by solving one of the least glamorous, but most critical, problems in AI: data quality. For the vast majority of teams, preparing high-quality training data is the most costly and time-consuming part of bringing AI products to market, and it ultimately determines whether models succeed or fail. As former computer scientists, physicists, and quants, we experienced this pain firsthand. AI today feels like the early days of the internet — huge potential, but immature tooling holding real progress back. That gap is why we s...

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...

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 buildin...

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 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...