About the company
Our client is an AI investment advisory and technology company, headquartered in the UK, that emulates human decisions in finance and portfolio management through its proprietary Artificial Intelligence (AI) Engine. The AI Engine is used to evaluate and forecast investment opportunities in the financial markets, and is architected as a massively parallel and distributed system spread across thousands of machines in multiple datacenters. The company’s mission is “General AI for finance” as well as always incorporating sustainability factors within its investment strategies.
The company is majority-owned by its parent group, a global group of fintech companies providing a range of sustainable investment and data services.
With headquarters in London and offices in Frankfurt, Singapore, and Boston, and following a Series A round, the firm is in a period of rapid international growth.
They have open a range a levels of Seniority from PhD level 3-6 month internships right through to full time associate and director roles. The salary package for full time roles is competitive.
The AI team primarily works on the company’s AI engine which delivers investment recommendations for the purposes of fund management. We have over 50 R&D projects in the pipeline with an ultimate goal of building a 'general AI' engine within the financial space. Our work covers a broad spectrum of science-based fields deploying approaches from Supervised and Unsupervised Learning, Feature Engineering, Natural Language Processing, Ensemble Methods, Network Analysis, Bayesian Approaches, Signal Processing, Portfolio Optimisation, Agent Based Modelling and Swarm Intelligence. We are looking for candidates with research experience in one or more of these fields.
We are also interested in high performance and distributed computing candidates. Candidates would ideally be familiar with one or more of the following tech stacks: Apache Cassandra, Kafka, Spark, Kubernetes, Cloud Computing (AWS, Google, Azure). We also employ various object store and database systems. Experience with computational graphs is a plus.
While candidates are not required to have a knowledge of finance and professional experience is not a necessity, candidates would have ideally engaged in personal side projects or the open source community.
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