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Software Developer - Machine Learning Infrastructure

Squarepoint Capital
London
7 months ago
Applications closed

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Squarepoint is a global investment management firm that utilizes a diversified portfolio of systematic and quantitative strategies across financial markets that seeks to achieve high quality, uncorrelated returns for our clients. We have deep expertise in trading, technology and operations and attribute our success to rigorous scientific research. As a technology and data-driven firm, we design and build our own cutting-edge systems, from high performance trading platforms to large scale data analysis and compute farms. With offices around the globe, we emphasize true, global collaboration by aligning our investment, technology and operations teams functionally around the world.

Role: Software Developer - Machine Learning Infrastructure

Team: Data Products

Department: Data Development

Squarepoint is looking for a range of Software developers with strong technical skills for the Machine Learning Infrastructure team.

You will be part of a team that designs, builds and maintains several backend applications and frameworks used by quants and traders, who they work closely with day to day. The team has multi-year roadmaps and are tasked with developing flexible, scalable, and well-designed systems that can accommodate future new features. 

The role will involve working closely with data scientists and ML researchers as well as other developers to architect, design, build and maintain our constantly evolving ML infrastructure and ultimately be accountable for it along with your team. While we’re ultimately looking for software developers, having an interest in ML infrastructure or previous experience in the field is highly desirable.

Position Overview:

Take stock of any existing code base, work on consolidation and streamlining of repositories and propose an internal technical roadmap. Work closely with our investment stakeholders and quantitative researcher to maintain alignment with their requirements. Build and maintain scalable, tested, production grade systems and infrastructure for containerization, deployment, versioning, testing and monitoring of ML models and more.  Take full ownership of the products you and your team work on to ensure continued support and improvements. Support and troubleshoot live production systems. Willingness to pick up and learn new software, ML technologies and tools used by data scientists.

Required Qualifications:

Bachelor’s degree in computer science, Engineering, or related subject Minimum of 5 years of fulltime software development experience Experience with highly available distributed systems and working with large datasets High proficiency in Python and/or Rust Kubernetes experience Experience working in a Linux environment, using version control. 

Nice to have:

Experience with Vector storage and search for generative AI Exposure to any of the following: SLURM, PostgreSQL Cloud (AWS or GCP) exposure Basic knowledge of financial markets Experience with gRPC, Apache Arrow Experience with ML frameworks such as PyTorch and TensorFlow Experience with ML infrastructure frameworks like Kubeflow, MLFlow etc Basic knowledge of financial markets
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