Distributed Systems/ML Engineer
Platform – Remote, Global
About the team
At Paperclip, we are a dedicated team of innovators, engineers, and visionaries committed to driving sustainable and efficient solutions across various industries. Our collective expertise spans automotive technology, artificial intelligence, and insurance, allowing us to develop groundbreaking products that address some of the world’s most pressing challenges. United by a common mission to expedite progress and reduce environmental impact, our team works tirelessly to turn ambitious ideas into reality.
From revolutionizing the internal combustion engine with Paperclip Automotive, to accelerating software development with PaperclipAI, and creating smarter insurance solutions with Paperclip Insurance, we strive to make a lasting positive impact on both our planet and society.
About the role
As a Distributed Systems/ML Engineer at Paperclip, you will enhance the performance and scalability of our machine learning systems, enabling researchers to experiment with new ideas and push the boundaries of AI. This role demands excellent engineering skills to design, implement, and optimize state-of-the-art AI models, write bug-free machine learning code, and gain a deep understanding of distributed systems and performance optimization.
We’re looking for people who love optimizing performance, understanding distributed systems, and cannot stand having bugs in their code. Since our systems handle large-scale machine learning workloads, performance improvements will have a significant impact.
This role is remote and available globally, offering flexibility and the opportunity to work with a diverse team from around the world.
In this role, you will:
- Apply the latest techniques to optimize our distributed machine learning systems for impressive hardware efficiency.
- Profile and optimize our machine learning pipelines.
- Collaborate with researchers to enable the development of the next generation of AI models.
You might thrive in this role if you:
- Have run small-scale ML experiments.
- Love figuring out how systems work and continuously come up with ideas to make them faster while minimizing complexity and maintenance burden.
- Have strong software engineering skills and are proficient in Python.