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Software Engineer III

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Systems Integration Solutions, Inc.

Cupertino, CA (In Person)

$197,600 Salary, Full-Time

Posted 2 days ago (Updated 16 hours ago) • Actively hiring

Expires 6/8/2026

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Job Description

Job Description Sr Backend Software Engineer -
Data & ML Innovation Location:
Cupertino, CA W-2 Only | No C2C | No Sponsorship Long-term Contract Pay rate: $95/HR Summary Join a cutting-edge AI/ML organization focused on improving Foundation Models through large-scale data innovation. This team leverages data from a variety of sources including licensed, vendor, crawl, and internal datasets to optimize model training efficiency and performance. We are seeking a Senior Backend Software Engineer with deep Python expertise and experience building scalable backend systems, pipelines, and data services supporting large-scale AI/LLM workflows. Responsibilities Develop large-scale training data pipelines for AI/ML systems Convert raw data into formats compatible with training jobs across GCP and AWS environments Support large-scale inference workflows using fine-tuned LLMs Build scalable backend services and REST APIs for data access and inspection tools Process and filter massive, often messy datasets efficiently Leverage open-source and internal tooling to improve model training and inference performance Collaborate cross-functionally with engineering teams to drive backend innovation and scalability Minimum Qualifications BS in Computer Science, Electrical Engineering, or equivalent technical degree 10+ years of professional Python development experience Strong understanding of: Concurrency & parallelism Functional programming Decorators Data structures & algorithms Object-oriented programming Experience building scalable applications and distributed systems Proficiency with REST APIs, Redis, VectorDBs, or other large-scale data storage technologies Experience designing, testing, reviewing, and deploying production-scale software systems Preferred Qualifications Experience with streaming/data processing technologies such as Kafka Familiarity with tools such as Docker, Jenkins, Maven, and Gradle Exposure to GCP and AWS environments Experience supporting AI/ML or LLM-related infrastructure and workflows Strong architecture and system design experience Excellent communication and cross-functional collaboration skills Self-motivated, curious, and comfortable working in ambiguous, fast-paced environments

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