Senior AI Engineer
Tasks
- Define scalable APIs for enterprise AI systems
- Design LLM inference prototypes for IBM Z
- Design benchmarking and profiling methodologies
- Design observability and telemetry for AI workloads
- Design runtime architectures for large scale AI workloads
- Develop AI integration frameworks
- Develop monitoring dashboards and reporting models
- Drive root cause analysis for performance regressions and stability issues
- Evaluate performance scalability reliability trade offs
- Identify optimization opportunities for hardware acceleration and batching
- Lead AI and LLM technology research
- Lead AI inference performance investigations
- Produce technical documentation and design proposals
- Provide technical leadership and architecture reviews
Perks/Benefits
- N/A
Skills/Tech-stack
Benchmarking | C# | C++ | CI/CD | Distillation | Distributed Systems | Docker | ELK | Grafana | Hardware acceleration | Hugging Face | Hugging Face Transformers | Inference | Kubernetes | Language Models | Large Language Models | Linux | Memory Optimization | Model Optimization | Monitoring | ONNX Runtime | Observability | OpenTelemetry | Parallel processing | Performance Analysis | Profiling | Prometheus | Pruning | PyTorch | Python | Quantization | Resource orchestration | Splunk | System Architecture | Telemetry | TensorFlow | TensorRT | Torchserve | Transformer | VLLM
Education
Roles
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