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devopsroles

Junior SRE

Squarepoint Capital Open · verified Oct 24, 2026
New York Junior Site Reliability

At a glance

Junior Site Reliability role at Squarepoint Capital. New York · $150,000 base.

SalaryStated by Squarepoint Capital
$150,000
Base salary for this role, in USD per year, as published in the posting.
RoleSite Reliability
SeniorityJunior
LocationNew York
Base pay$150,000
PostedJul 23, 2026 · 3mo ago
Role brief

devopsroles summary, based on the employer's posting.

What you'll do

  • Build and maintain data flows that support machine learning training and inference
  • Improve platform components for scheduling, resource allocation, data movement and filesystems
  • Find performance bottlenecks and help systems handle larger workloads
  • Strengthen reliability, monitoring and usability across ML or HPC platforms
  • Turn researchers’ and developers’ needs into practical technical solutions

What you bring

  • A computer science, engineering or applied mathematics degree, or comparable hands-on experience
  • Strong grounding in algorithms, data structures and operating systems, with distributed systems knowledge
  • Software development experience in Python, C++ or Rust, including writing and maintaining production-ready code
  • Experience using Linux and familiarity with ML workflows, data engineering or ML platforms

Who this fits

This junior, full-time role suits someone early in their career who wants to work on infrastructure, performance and large-scale systems. You’ll learn existing platforms, contribute to ongoing work and take on more ownership with guidance from experienced engineers. The role is based in New York, where the stated minimum base salary is $150,000 per year.

From the employer

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.

Opportunity

Site Reliability work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Site Reliability$150k+

Find me work

By the team behind devopsroles.

Find me work
Opportunity

Site Reliability work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind devopsroles.