At Sense Street, we are developing natural language understanding systems for capital markets. Our premise is simple: markets are conversations, and we help investment banks and asset managers have better, more efficient conversations.

Through our partnerships with global banks, we have access to datasets that have not been made available in the past. This allows us to create language models uniquely suited to capital markets while advancing the state-of-the-art. We are a venture backed company founded by professionals with experience spanning machine learning, trading, and quantitative research.

The Role

We’re looking for a data-savvy software engineer who thrives on solving new and unexpected challenges — building bespoke software, APIs, data pipelines, and platform components that bring AI capabilities to life. To do this you’ll work closely with our data scientists and product designers as part of our tech team that’s critical in deploying, integrating, and supporting the systems that connect it all together.

On a practical level, you’ll work closely with our data scientists (and sometimes end-users) to bring AI systems into the real world. That could mean shaping how a new model is integrated, debugging a system bottleneck, or helping internal teams and customers get more value from model outputs as needs evolve.

Requirements

• Proven experience designing and building robust backend systems using technologies such as Node.js, Python, MongoDB, PostgreSQL, Redis, RabbitMQ, and Kafka
  
• Demonstrated ability to scale production systems in cloud-native environments, familiarity with Kubernetes, NGINX, and container orchestration
• Experience building and maintaining
  real-time applications, including working with WebSockets and event-driven architectures
  
• Understands that solving problems means working across the stack from API development to frontend UIs and infrastructure-as-code
• Have built real-world systems that expose or depend on ML models, including deployment or inference tooling (e.g. model serving, feature stores)
• Think in terms of use cases and outcomes, not just infrastructure and moving data
• Strong software engineering fundamentals, with deep knowledge of algorithms, data structures, and system design
  

Nice to Have

• Built tools or interfaces for internal teams (e.g. dashboards, annotation tools, developer APIs)
• Experience with JavaScript/TypeScript, with experience developing user-facing features using React
  

The Work Environment

• Flexible working, central London location
• Highly skilled team, flat hierarchy, and opportunities for mentorship
• Ability to heavily influence platform and culture in a scaling company
• Budget/time for books, training and attending conferences/hackathons
• Opportunity to work with cutting-edge AI technologies and unique datasets
• Regular knowledge sharing sessions and internal tech talks

Company Benefits

• Flexi Working
• Pension
• Laptop
• Hybrid working - home/office
  
• Share Options Scheme
• Private Healthcare