Bayside Solutions

Backend Software Engineer: Python-PyTorch

in Cupertino, California

Job Description Job Attributes+

  • Req ID

    25129_1769728809

  • Job Category

    IT

  • Job Type

    Contract

  • Hourly Salary

    From $0 to $0

  • Job Location

    Cupertino, California
    United States

Overview

Backend Software Engineer: Python-PyTorch

W2 Contract

Salary Range: $114,400 - $135,200 per year

Location: Cupertino, CA - Remote Role

Job Summary:

We are seeking experienced AI / ML Infrastructure Engineers to join a central ML/AI platform team responsible for building foundational services used by multiple internal and external product organizations. This role focuses on designing, extending, and supporting scalable ML infrastructure that powers both traditional machine learning and modern LLM-based workflows.

Duties and Responsibilities:

  • Design, develop, and enhance ML infrastructure services supporting training, inference, experimentation, and embeddings lifecycle management.
  • Implement small to medium-sized features across existing ML platform components.
  • Take customer use cases end-to-end, including investigation, debugging, and resolution of issues.
  • Work across the ML stack, collaborating closely with applied scientists and downstream product teams.
  • Diagnose and resolve issues in production ML systems.
  • Navigate ambiguous requirements and proactively unblock work by seeking context or collaboration when needed.
  • Clearly communicate technical decisions, trade-offs, and implementation rationale.

Requirements and Qualifications:

  • Strong experience with Python, including writing production-quality, maintainable code
  • Hands-on experience with PyTorch in real-world ML systems (training and/or inference)
  • Solid understanding of ML fundamentals, including:
  • Model training vs inference
  • Embeddings and representation learning
  • Experimentation and evaluation workflows
  • Experience debugging and maintaining complex, distributed systems
  • Ability to reason through problems, explain solutions, and articulate trade-offs
  • Comfort operating in environments with ambiguity and incomplete requirements

Preferred Qualifications:

  • Experience building or supporting ML infrastructure platforms
  • Familiarity with feature stores, experimentation frameworks, or inference services
  • Exposure to large-scale, multi-team ML environments
  • Prior work supporting both research and production ML use cases

Bayside Solutions, Inc. is not able to sponsor any candidates at this time. Additionally, candidates for this position must qualify as a W2 candidate.

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