AI/ML Customer Engineer
Tasks
- Build reference codebases
- Collaborate on joint architecture validation
- Create open-source AI quickstarts
- Design production-ready architecture blueprints
- Develop automated testing and evaluation harnesses
- Implement system telemetry for monitoring
- Incorporate data privacy and secure network perimeters
- Integrate solutions across system stack
- Measure latency throughput cost and model quality
- Package repeatable extensible architectures
- Support localized hosting compliance
Perks/Benefits
- Access to emerging hardware technologies
- Open Source contribution
- Remote work flexibility
- Technical career growth
Skills/Tech-stack
Agentic Workflows | Air-gapped | Air-gapped networks | C# | C++ | CI/CD | CUDA | Clean Code | Computer Vision | Container Security | Datasets | Git | Go | Hugging Face | Hugging Face Transformers | Kubeflow | Kubernetes | LLM orchestration | Langchain | Langgraph | Language Processing | Llamaindex | MLOps | MLflow | Machine Learning | Model Context Protocol | Model Serving | Natural Language | Natural Language Processing | Network Security | PEFT | PyTorch | Python | ROCm | Ray | SFT | Secure Registries | Test-Driven | Test-Driven Development | Tokenizers | VLLM | Vector Databases
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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