Member of Technical Staff (MTS), Machine Learning, SMAI
Tasks
- Architect and execute model training jobs
- Build and maintain data and solution pipelines
- Create and maintain CI/CD pipelines for AI solutions
- Design and deploy autonomous AI agents
- Design and optimize data structures in data systems
- Optimize training throughput and memory efficiency
- Orchestrate LLM interactions with tools and APIs
- Profile and debug GPU performance bottlenecks
Perks/Benefits
- N/A
Skills/Tech-stack
Agentic AI | Autogen | Automl | BF16 | Big Data | Big data processing | C plus plus | CI/CD | CUDA | CUDA programming | Chain-of-Thought | Cloud platform | DDP | Data Pipelines | Data Processing | Data-parallel | Distributed Data Parallel | Distributed Training | Distributed data | Docker | ETL | FP16 | FP8 | FSDP | Fully Sharded Data Parallel | Function Calling | GPU Architecture | GenAI | Git | Google Cloud | Google Cloud Platform | Inference Optimization | Java | Jenkins | Kubeflow | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | LoRA | Machine Learning | Mixed Precision | Model Parallelism | Nsight Systems | PEFT | Prompt engineering | PyTorch | PyTorch Profiler | Python | QLoRA | Ray | Slurm | Snowflake | TensorRT-LLM | Tool use | Triton | VLLM
Education
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