What are the responsibilities and job description for the Python Developer position at Systems Integration Solutions?
Sr Backend Software Engineer – Data & ML Innovation
📍 Location: Cupertino, CA
💼 W-2 Only | No C2C | No Sponsorship
⏳ Long-term Contract
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 (firm requirement, cannot substitute for a data science 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