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 AI. AI today is what the early days of computing or the internet were like, where the potential of the technology is clear, but the tools and processes surrounding it are still primitive, preventing the next generation of applications. This is why we started Encord.
We are a talented and ambitious team of 90+, working at the cutting edge of computer vision and deep learning, backed by top investors, including CRV and Y Combinator, leading industry executives like Luc Vincent, former VP of AI at Meta, and other top Bay Area leaders in AI. We are one the fastest growing companies in our space, and consistently rated as the best tool in the market by our customers. We have big plans ahead and are looking for a Machine Learning Engineer to join us our ML team.
We are looking for an experienced Machine Learning Engineer to help us conduct research on the state of the art of computer vision and solve multifaceted algorithmic problems. You will:
The role will be exposed to a broad tech stack (e.g. ReactJS, Python, REST & GraphQL, OpenCV, PyTorch, GCP, AWS & CUDA, Kubernetes) and the cutting edge of computer vision and deep learning.
The right candidate will have a proven track record of relevant publications and previous experience managing applied research teams. Requirements for the role include:
Encord offers a unique opportunity to be part of a startup with a clear mission and vision. You will get to explore and build services enterprise AI use cases across many different industry verticals such as healthcare, surveillance, retail, agriculture, and many more.
Our work is at the cutting edge of computer vision and deep learning, which also includes working on solving unsolved problems within those fields.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Encord is the multimodal data labeling, curation and evaluation platform for AI. With Encord, AI teams can easily manage, curate, and label images, videos, audio, documents, text, LiDAR, 3D point cloud, and DICOM files on one unified platform while benefiting from AI-assisted speed and accuracy with human-in-the-loop workflows. Enrich petabytes of raw unstructured data into high-fidelity data for training, fine-tuning, and aligning AI models quickly and at scale.
Encord is trusted by pioneering AI teams at Synthesia, Captions AI, Tractable, Stanford Medicine, Flock Safety, Protex AI, Zoopla, Philips, and many more global companies.
Confidentially build production AI with rich multimodal data. Encord is SOC 2, AICPA SOC, HIPAA, and GDPR compliant.
