Vector.ai is a machine learning start-up on a mission to transform document-driven operations in the supply chain and shape the future of inter-company and ‘inter-national’ trade. An applied AI company, we’re combining bleeding-edge machine learning research with a zealous focus on the customer; everything we do - across our stack - is informed by real-world operational insights. Our customers are some of the largest companies in the world, but our ambition is to help some of the most under-served companies too.
We've recently raised our seed round from leading UK investor Episode 1 (Zoopla, Betfair, Shazam, etc.) and supply chain-focused fund Dynamo.vc.
We’re searching for a Machine Learning Engineer to lead our efforts in remaining at the bleeding edge of machine learning by spearheading the implementation of machine learning models in production across the technology stack. You will also be involved in contributing to and overseeing the build and deployment of machine learning models into a highly scalable, distributed system along with the rest of the team. You will also work with our customers and their teams to implement solutions that improve their results.
Specifically we want someone who can:
- Implement and develop machine learning models in a scalable product architecture
- Establish a data management pipeline to dynamically update core algorithms
- Bring machine learning systems into full production, working closely with members of the product and engineering teams
- Optimize existing implementations of machine learning models in production
- Optimize open source implementations of research code to production ready systems
- Communicate clearly, both with internal teams and customers.
Skills we expect:
- Work with python and a few common machine learning frameworks, including but not limited to tensorflow, keras and pytorch
- Have experience building and deploying machine learning applications at scale
- Have a very solid grasp of both software engineering and machine learning fundamentals.
Experience that would be good to have:
- Grasp of the fundamentals of all major aspects of modern artificial intelligence - computer vision, natural language processing, reinforcement learning, etc.
- 2+ years industry experience building and deploying machine learning applications
- Be familiar with working on real-world unstructured and noisy datasets
- Good understanding of MLOps practices