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Backend Software Engineer: Python-PyTorch

Bayside Solutions
Department:Backend Developer
Type:REMOTE
Region:USA
Location:Santa Clara, CA
Experience:Mid-Senior level
Salary:$114,400 - $135,200
Skills:
PYTHONPYTORCHMACHINE LEARNING INFRASTRUCTUREAI/ML PLATFORMSMODEL TRAININGMODEL INFERENCELLM WORKFLOWSEMBEDDINGSREPRESENTATION LEARNINGEXPERIMENTATION FRAMEWORKSML EVALUATIONINFERENCE SERVICESFEATURE STORESDISTRIBUTED SYSTEMSSCALABLE SYSTEMS DESIGNPRODUCTION ML SYSTEMSDEBUGGING AND TROUBLESHOOTINGML PLATFORM DEVELOPMENTINFRASTRUCTURE SERVICES
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Job Description

Posted on: February 21, 2026

Backend Software Engineer: Python-PyTorchW2 ContractSalary 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

Desired Skills and Experience

Python, PyTorch, Machine Learning Infrastructure, AI/ML Platforms, Model Training, Model Inference, LLM Workflows, Embeddings, Representation Learning, Experimentation Frameworks, ML Evaluation, Inference Services, Feature Stores, Distributed Systems, Scalable Systems Design, Production ML Systems, Debugging and Troubleshooting, ML Platform Development, Infrastructure Services, End-to-End Problem Solving, Cross-Functional Collaboration, Applied Science Collaboration, Research-to-Production ML, Ambiguous Requirements Handling, Technical Communication, Trade-off Analysis, Maintainable Production Code

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

Bayside Solutions, Inc. may collect your personal information during the position application process. Please reference Bayside Solutions, Inc.'s CCPA Privacy Policy at www.baysidesolutions.com.

Originally posted on LinkedIn

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