{"id":951678,"url":"https://alion.io/job/squarepoint-junior-sre","title":"Junior SRE","company":{"id":684807,"name":"Squarepoint Capital","domain":"squarepoint-capital.com","url":"https://alion.io/company/squarepoint-capital","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"C","score":61,"open_postings":76,"ghost_share":0.658,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":40,"computed_at":"2026-10-16T05:45:00Z"}},"role":"DevOps","role_family":"DevOps","seniority":"junior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":43000,"max_usd":84000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":40},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"C++","optional":false},{"name":"HPC","optional":false},{"name":"Linux","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Rust","optional":false},{"name":"CUDA","optional":true},{"name":"CUDA Toolkit","optional":true}],"status":"live","first_seen_at":"2026-07-23T20:34:49Z","employer_posted_date":"2026-08-06","last_verified_at":"2026-10-16T21:50:35Z","board_verified":true,"closed_at":null,"days_open":85,"trust":{"level":"ok","repost_count":0,"flags":["company_stale"],"days_open":84},"description":"Position Overview:\nThis 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.\nAs 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.\nThis role is designed to offer strong mentorship while encouraging increasing autonomy and technical ownership over time.\nAs part of the team, you will work on some of the following:\nDesign, implement, and maintain data pipelines for machine learning training and inference.\nDevelop and improve workflow orchestration and infrastructure components (e.g. scheduling, resource allocation, data movement, filesystems).\nAnalyze and improve performance and scalability of systems and critical code paths.\nImprove the reliability, observability, and usability of ML or HPC platforms.\nCollaborate with quantitative researchers and developers to understand requirements and translate them into robust technical solutions.\nThe opportunity to work on production-grade ML and HPC infrastructure at scale.\nStrong mentorship and technical guidance from experienced engineers.\nGradual ownership of meaningful systems and components.\nExposure to real-world performance, scalability, and reliability challenges.\nClose collaboration with quantitative researchers and developers.\nYou 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.\nRequired Qualifications\nA degree (BSc or MSc) in Computer Science, Engineering, Applied Mathematics, or a related field, or equivalent practical experience.\nStrong foundations in computer science (e.g. algorithms, data structures, operating systems, distributed systems).\nExperience developing software in at least one language such as Python, C++, or Rust.\nFamiliarity with writing, testing, and maintaining production-quality code.\nAbility to reason clearly about technical problems and communicate effectively with teammates.\nInterest in infrastructure, performance, and large-scale systems.\nExposure to machine learning workflows, data engineering, or ML platforms.\nExperience working in Linux environments.\nIntroductory knowledge of distributed systems, HPC, or cloud platforms for CPU and GPU workloads.\nExperience with profiling, benchmarking, or performance analysis.\nAdditional Qualifications (Nice to Have)\nFamiliarity with CUDA or other GPU development frameworks.\nThe 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. 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