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Salary
≈ $43k – $84k per year (Estimated)
Location
In office (New York)
Seniority
Junior

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Jul 23, 2026. Squarepoint Capital scores C on the Alion truth index.

Overview
Company
Impact
Profile match
Squarepoint Capital is a global quantitative investment manager that runs systematic trading strategies across equities, fixed income, foreign exchange, commodities and derivatives, built on in-house research, execution and portfolio management technology. Founded in 2014 as a spin-out of the quantitative trading business of Deutsche Bank, it operates offices in North America, Europe and Asia-Pacific, including New York, Montreal, Singapore, Bengaluru and Geneva. The firm is headquartered in London, England, United Kingdom.

Position Overview:

This is a Full-time Junior Software Engineering position for candidates early in their career who are interested in infrastructure, systems, and machine learning platforms at scale.

As a Junior Engineer, you will contribute to production ML/HPC infrastructure, working alongside experienced engineers and quantitative researchers. You will gradually take ownership of components and features, learn how large-scale systems are designed and operated in practice, and contribute production-quality code that directly supports research and trading workloads.

This role is designed to offer strong mentorship while encouraging increasing autonomy and technical ownership over time.

As part of the team, you will work on some of the following:

  • Design, implement, and maintain data pipelines for machine learning training and inference.
  • Develop and improve workflow orchestration and infrastructure components (e.g. scheduling, resource allocation, data movement, filesystems).
  • Analyze and improve performance and scalability of systems and critical code paths.
  • Improve the reliability, observability, and usability of ML or HPC platforms.
  • Collaborate with quantitative researchers and developers to understand requirements and translate them into robust technical solutions.
  • The opportunity to work on production-grade ML and HPC infrastructure at scale.
  • Strong mentorship and technical guidance from experienced engineers.
  • Gradual ownership of meaningful systems and components.
  • Exposure to real-world performance, scalability, and reliability challenges.
  • Close collaboration with quantitative researchers and developers.

You will be expected to learn existing systems, contribute independently to ongoing work, and progressively take ownership of well-defined areas of the platform with support from more senior engineers.

Required Qualifications

  • A degree (BSc or MSc) in Computer Science, Engineering, Applied Mathematics, or a related field, or equivalent practical experience.
  • Strong foundations in computer science (e.g. algorithms, data structures, operating systems, distributed systems).
  • Experience developing software in at least one language such as Python, C++, or Rust.
  • Familiarity with writing, testing, and maintaining production-quality code.
  • Ability to reason clearly about technical problems and communicate effectively with teammates.
  • Interest in infrastructure, performance, and large-scale systems.
  • Exposure to machine learning workflows, data engineering, or ML platforms.
  • Experience working in Linux environments.
  • Introductory knowledge of distributed systems, HPC, or cloud platforms for CPU and GPU workloads.
  • Experience with profiling, benchmarking, or performance analysis.

Additional Qualifications (Nice to Have)

  • Familiarity with CUDA or other GPU development frameworks.

The minimum base salary for this role is $150,000 if located in New York.  This expectation is based on available information at the time of posting.  This role may be eligible for discretionary bonuses, which could constitute a significant portion of total compensation.  This role may also be eligible for benefits, such as health, dental, and other wellness plans, as well as 401(k) contributions.  Successful candidates’ compensation and benefits will be determined in consideration of various factors.

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