Staff AI Engineer
Tasks
- Build golden datasets for evaluation
- Collaborate with product and business teams
- Create data pipelines for training and validation
- Curate and sanitize large scale datasets
- Deploy and operate scalable inference services
- Evaluate closed versus open model ecosystem strategies
- Fine tune and distill language models
- Generate synthetic data
- Implement LLM as a judge evaluation
- Lead applied machine learning research
- Manage end-to-end model lifecycle
- Mentor engineers and provide technical leadership
- Monitor inference workloads in cloud environments
- Optimize LLM inference latency
- Orchestrate microservices for ML inference
- Quantize models for efficient serving
- Translate research findings into product features
Perks/Benefits
- N/A
Skills/Tech-stack
APIs | BigQuery | CUDA | Cloud infrastructure | Cloud platform | Data Curation | Dataset Management | Deep learning | Distributed Systems | Efficient Fine Tuning | Fine Tuning | GPU Acceleration | Golden Dataset | Google Cloud | Google Cloud Platform | Google Kubernetes | Google Kubernetes Engine | Inference Optimization | Kubernetes | Kubernetes Engine | LLM Evaluation | LLM-as-a-Judge | Language Models | Large Language Models | LoRA | Low Latency | Low-Latency Systems | Machine Learning | Microservices | Model Distillation | Parameter efficient fine-tuning | PyTorch | Python | Q LoRA | Quantization | Synthetic data | Vertex AI
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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