Our mission at Glyphic is to make finding, creating, and sharing enterprise information as easy as possible. We’re starting by building powerful, intuitive products that help elite revenue teams sell more effectively by equipping them with the collateral and intelligence they need to navigate complex customer discussions.
We are intimately familiar with recent transformational changes in deep learning, NLP, and generative AI as former researchers and operators at top AI research labs and companies. Now, we think it’s the right time for these advances to power a new generation of AI-copilot tools that make enterprises feel superhuman.
Founders Adam Liska and Devang Agrawal previously worked with large language models at DeepMind and built AI-augmented products at companies like Apple and Spotify. We’re putting together an elite team of technologists and operators to help us achieve our ambitious vision.
We’re well-funded and backed by world-class investors and advisors.
About the role
We are looking for team members who are excited by translating state-of-the-art research into products and enjoy building from the ground up.
Machine learning is central to our efforts in building next-generation products. As a Machine Learning Engineer at Glyphic, you will be at the forefront of applications powered by large deep learning models. As an example, in this role you may develop conversational understanding and constrained text-generation models, test them with users, and apply them in production.
What you’ll do
Collaborate with a cross-functional team to design innovative solutions to user problems and push the boundary of what’s currently possible.
Run experiments, evaluate and communicate results, and draw conclusions to inform production decisions.
Design, train, deploy, and scale ML models from 0 to 1 in the cloud.
Maintain production models.
Contribute to the development of shared machine learning infrastructure.
Stay up-to-date with new developments in ML research and constantly think about how these could be incorporated into our products.
Who you are
You have a degree in a quantitative field or relevant experience.
You have experience designing, training, and evaluating machine learning models using standard frameworks (for example, PyTorch, TF, JAX).
You have hands-on experience implementing and supporting production machine learning systems at scale in Python.
You have experience in data processing (for example, using Apache Beam) and analysis.
Previous experience with Natural Language Processing is a plus.
You understand the goals and practices of MLOps and have experience with cloud platforms like GCP or AWS.
What you’ll get
Exciting work at the forefront of applied machine learning in a well-funded startup.
Competitive salary and share options.
25 days of paid time off and flexible public holidays.
Professional development allowance (for example, for conference or course attendance).
We are primarily based in London and meet in the office at least once a week. We can consider more flexible arrangements on a case by case basis.