At nibble, we’re building the next generation of technical tools for data science in production. We feel lucky to be working in this exciting space with incredible challenges waiting to be solved at scale.
We are opening a full-time/full-remote Machine Learning Engineer position. Preferably in the European Union (or similar time zones) 🇪🇺.
Founded in 2018, we’re solving the challenges posed by the industrialisation and scaling of data-centric algorithmic processes.
Funded by our ability to design and sell our solutions. Fuelled by a blend of creativity and technical expertise. Driven by an uncommon approach in a stimulating environment. Our hybrid model combines services (consulting, hands-on technical assistance) with the development and integration of custom in-house software solutions.
We’re a small team working remotely from European cities (France, Portugal, Germany), looking for singular individuals to build with us the next generation of tools for data science in production.
→ "Festina Lente"
We are biased towards people of action who know how to take the time to reflect. Paradoxical? Yet it is our driving force. This is embodied in our constant focus on building foundations, emphasizing density over quantity, knowing that these choices will be fruitful in due time.
It's not that I'm so smart, it's just that I stay with problems longer.
→ We are problem solvers, not glitter sellers
Formulate the problems. Take the risk. Solve any malfunctions. Focus on the value generated. No room for glitter and wasted billed time. Hype is not a metric we use. We always favor simplicity over over-engineered and complex approaches.
See Simple Made Easy, a talk by Rich Hickey (creator of the Clojure language).
→ Unconventional thinking
We like to believe we’re building a team of exceptional people, endowed with sharp and independent thinking who stimulate people around them. We are not looking for consensus, but rather to reach higher grounds with discussion between individuals who have opinions, and are able to defend or drop them based on a constant flow of inputs.
See Paul Saffo's essay Strong Opinions Weakly Held.