Python Software Engineer (Jr-Mid Level)
6 months, with potential extension or conversion
Fremont, CA — 5 days onsite
Role Summary
We are seeking a junior to mid‑level Python Software Engineer (3-5 years experience) to design, build, and optimize data‑intensive applications and machine learning solutions. The ideal candidate will come from fast‑paced technology companies (Amazon, Google, Microsoft, PayPal, Uber, Airbnb, Doordash, Expedia, etc.) and have a concise resume highlighting hands‑on coding contributions, debugging, troubleshooting, and distributed systems experience.
This role requires strong engineering fundamentals, recent hands‑on development, and the ability to clearly articulate technical contributions.
Responsibilities
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Design, develop, and deploy LLM‑powered and AI‑driven applications.
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Build scalable, high‑performance solutions using Python and modern engineering practices.
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Develop and maintain REST APIs and microservices supporting critical business operations.
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Work with diverse data sources (text, voice, image, structured datasets).
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Collaborate with cross‑functional teams to identify opportunities for automation and optimization.
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Own production systems: monitoring, troubleshooting, and continuous improvement.
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Translate ambiguous business requirements into end‑to‑end technical solutions.
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Write clean, maintainable, and reusable code following agile practices.
Must‑Have Requirements
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3-5 years of professional software engineering experience.
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Bachelor’s or Master’s in Computer Science, Engineering, or equivalent practical experience.
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Strong hands‑on Python experience for data‑intensive and high‑performance applications.
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Experience building and deploying production machine learning solutions.
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Demonstrated work with Large Language Models (LLMs) and Generative AI.
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Experience developing REST APIs and microservices.
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Proficiency with MySQL and Redis.
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Familiarity with at least one deep learning framework (PyTorch, TensorFlow, JAX).
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Strong fundamentals in statistics, data analysis, model evaluation, and performance optimization.
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Clear examples of debugging, troubleshooting, and distributed systems problem‑solving.
Nice‑to‑Have Qualifications
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Experience with recommender systems, operations research, or advanced AI/ML solutions.
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Building and supporting enterprise‑scale ML platforms.
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Working with large, complex datasets in production environments.
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Knowledge of C# and ASP.NET (secondary skill).
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Prior experience automating compliance frameworks and generating audit evidence.
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