Full time /
Large language models have brought about a paradigm shift to the way we think about the world. The potential of bringing human-level reasoning abilities to silicon is almost limitless. However, large scale enterprise adoption is still to happen. While significantly more efficient than humans for many tasks, the cost and latency of using LLMs at scale is still prohibitive by many orders of magnitude.
At Ntropy, our mission is to bring reasoning capabilities of the largest models into real world applications. This requires a fundamentally different approach to almost all parts of the model stack, including prompting, fine-tuning, monitoring, caching and deployment. For maximum performance, these need to be optimized for each task.
We have developed a new kind of domain-specific wrappers for language models, that leads to 4-6 orders of magnitude improvement in average entropy per token. The secret is breaking down complex problems into manageable segments, leveraging cached past responses to formulate answers to new queries.
The first domain we have been building for is finance. In early 2022, we released the first set of tools for extracting information from bank transactions. This challenge has traditionally demanded human expertise—accountants, underwriters, financial controllers, which restricted applications to only the most substantial transactions and left areas like small business lending and instant consumer credit scoring out of reach.
Using the Ntropy API, financial data can now be processed with super-human accuracy, scaling to cover over 4 billion daily electronic transactions globally. The result is a more equitable and efficient financial system for everyone.
In the near future, we will take what we have built for financial data to other domains, enabling anyone, from single developers to Fortune 500 companies, to run large language models at maximum effectiveness to solve the hardest and most impactful problems in the world. We are just at the beginning of our journey and you will be one of the early members of the team to shape this future with us.
- come from various fields - engineering, mathematics, physics and arts.
- are allergic to over-engineering.
- are anarchists at heart and like to hack around the status quo.
- love playing board and video games.
- are radically honest and appreciate challenging one another, rather than giving out “pats on the back”. Yet, we can always rely on each other for support, feedback and results.
- are willing to learn and adapt quickly to new situations and requirements. Languages, frameworks, libraries, compilers, etc. are just tools for a job. A new problem might need a new tool. If it doesn’t exist yet, we will build it.
- have a sense of humor (well, we think we do).
As an early member of our backend engineering team, you will help
- push the limits of distributed computing and orchestrating large-scale machine learning pipelines.
- build the team and drive the direction of the company.
- shape our product and culture.
- experience the real-world impact of what you build.
The following are a big plus
- past experience with React / Typescript stacks.
- recognized open-source contributions.
- at ease with data visualization tools.
- familiarity with machine-learning concepts and LLMs.
- experience with industry-standard databases, such as Postgres and Redis.
- strong understanding of data structures, algorithms and software-design principles.
What do typical frontend engineering tasks at Ntropy look like?
- developing, testing, and maintaining new and existing vertical analytics products on top of our core system, both the backend and frontend side.
- working in quick iterations with our customers to tune new products into great user experiences.
- working closely with our platform team and ML engineers to create the intelligence layers behind these new products.
- keeping up-to-date with the latest industry trends and suggesting new ways to improve our systems and processes.
Where is Ntropy located?
We have hubs in NYC, Lisbon and London. However, we are just starting our SF office and are hiring there for in-person roles only.
Do you consider part-time work?
Not at the moment. Full-time roles only.
How are you funded?
We are backed by some of the top funds in the world. Have raised double-digit millions of dollars so far. Can share more details over the call.
Do you already have a product and customers?
Yes. We have been in production since 1st Jan, 2022 and have in the high double digits customers using our APIs in production.
How big is your team?
We are around 20 people at the moment. Mostly engineering and product.
What is the interview process like?
1. Send us an overview of problems you have encountered before and how you approached solving them. Please include as much detail as possible: code, algorithms, derivations, proofs, etc. We will then do a video call to kick things off and go through it (45 mins).
2. We will give you a take-home project related to whatever we are currently working on (3-4 hours). Alternatively, if you have a relevant project that you worked on previously that demonstrates your skills as an engineer, you are welcome to use that instead.
3. We will then do a deep-dive through the project over a call and discuss the implementation, improvements and bottlenecks.
Above all, we respect your time and commitment and will keep you up to speed on where we are at during the whole process.
What are your hiring plans?
We expect to be 40-50 people by the end of 2024. Mostly engineering roles.
What is your current stack?
backend - Python, Rust
compute - AWS, GCP
ML - PyTorch, ONNX, Triton, LLMs
Work / life balance
We are a startup which requires you to put in a lot more work and soul than a regular job. We believe, however, that nothing easy is worth doing. We will expect a lot from you, and you should expect a lot from us.
What is the compensation?
approx. $130k • 0.1%