Backend Software Engineer: Python-PyTorch

Backend Software Engineer:
Python-Py Torch

W2 Contract

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

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.

• 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.

• 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:
• 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

• 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

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.

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