Senior AI Engineer
Tasks
- Conduct root cause analysis for performance and stability issues
- Define AI integration frameworks and platform integration patterns
- Design and prototype LLM inference workloads for IBM Z
- Design observability and telemetry for AI workloads
- Design scalable APIs and runtime interfaces
- Develop benchmarking and profiling methodologies
- Develop monitoring dashboards and operational intelligence
- Develop runtime architectures and resource orchestration
- Identify optimization opportunities for hardware acceleration
- Lead exploration of AI and LLM technologies for enterprise infrastructure
- Lead performance investigations for inference workloads
- Produce technical documentation and design proposals
- Provide technical leadership and architecture reviews
Perks/Benefits
- N/A
Skills/Tech-stack
Artificial Intelligence | Benchmarking | C# | C++ | CI/CD | Computer Architecture | Distributed Systems | Docker | Fault detection | Grafana | Hugging Face | Hugging Face Transformers | I/O | I/O systems | Kubernetes | LLM Inference | Language Models | Large Language Models | Linux | Machine Learning | Memory Management | Model Distillation | Monitoring | ONNX | ONNX Runtime | Observability | OpenTelemetry | Operating Systems | Parallel processing | Performance Engineering | Profiling | Prometheus | Pruning | PyTorch | Python | Quantization | Telemetry | TensorFlow | TensorRT | Torchserve | Transformer Architecture | VLLM
Education
Roles
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