At Encord, we're building the AI infrastructure of the future. Today, the biggest challenge companies face in getting an AI product to market is actually not half as glamorous as it may seem: 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.

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’re a team of 60 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 prominent 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.

About Us

Encord is a London-based startup building a comprehensive training data solution for computer vision AI applications. We are backed by CRV, Y Combinator Continuity, the Harvard Management Company, top industry executives, and other leading Bay Area investors.

Started by ex-computer scientists, physicists, and quants, we felt firsthand how the lack of tools to prepare quality training data was impeding the progress of building practical AI. AI feels to us like what the early days of computing or the internet must have felt like, where the potential of the technology is clear, but the tools and processes surrounding it are terrible. We have devised a unique methodology for automating the tasks related to preparing quality training data, in effect turning the training data problem into a data science problem.

The Role

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:

• Experiment with and adapt latest ML technologies to fit into existing tech stack

• Solve idiosyncratic statistical, geometric, and engineering problems

• Work closely with a full stack tech team to assist implementation of research solutions into the product

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.

Qualifications

The right candidate will have a proven track record of relevant publications and previous experience managing applied research teams. Requirements for the role include:

• Passion for solving ML problems

• Strong experience in Python and machine learning libraries such as OpenCV, PyTorch, TensorFlow, Fast.ai, and Keras

• Strong experience in mathematical programming, algorithmic problem solving, and applied machine learning

What We Offer

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, and agriculture.

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 offer competitive compensation and equity options in the business for the right candidate.

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.