Squarepoint Capital Logo

Squarepoint Capital

Junior SRE

Reposted 2 Months Ago
Be an Early Applicant
In-Office
Singapore, SGP
Junior
In-Office
Singapore, SGP
Junior
Early-career SRE working on production ML/HPC infrastructure: design and maintain data pipelines, orchestration, scheduling, performance and reliability improvements, and collaborate with researchers to deliver production-quality systems under mentorship.
The summary above was generated by AI

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.

Similar Jobs

8 Hours Ago
In-Office
Singapore, SGP
Senior level
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Senior technical leader driving equipment and hardware innovation, supplier engagement, and multi-year manufacturing capability roadmaps to enable high-volume semiconductor production, AI-enabled automation, and cost/productivity improvements across global front-end sites.
Top Skills: Advanced PackagingArtificial IntelligenceDramEquipment ArchitectureEquipment AutomationFront-End Semiconductor ManufacturingHeterogeneous IntegrationNandNorProcess Integration
8 Hours Ago
In-Office
Singapore, SGP
Mid level
Mid level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Lead development, characterization, optimization, and transfer of CMP processes for advanced 3D NAND. Coordinate with global teams and suppliers, run DOE experiments, troubleshoot manufacturing issues, evaluate consumables/hardware, drive process control and yield improvements, and contribute to innovation and documentation.
Top Skills: 3D NandAi ToolsCmpDoe
8 Hours Ago
In-Office
Singapore, SGP
Senior level
Senior level
Artificial Intelligence • Hardware • Information Technology • Machine Learning
Leads electrical failure analysis for next-generation NAND products, including bench testing, fault isolation, physical de-processing, and root-cause investigation of yield-limiting failures. Correlates electrical, probe, inline, parametric, and fab data; develops failure-analysis methodologies; applies analytics to identify trends and anomalies; and communicates findings through reports, visualizations, and technical presentations. Partners with process integration, yield enhancement, metrology, manufacturing, and data science teams to improve semiconductor yield and support technology transfer.
Top Skills: Data AnalyticsEdsEelsFibNandNorPhysical Failure AnalysisProbe Data AnalysisSemSemiconductor Process FlowTem

What you need to know about the Singapore Tech Scene

The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account