AI/ML Engineer (MLOps & LLM)
Tasks
- Build and maintain MLOps pipelines
- Collaborate with product and engineering teams
- Design, fine-tune, and evaluate LLMs
- Develop evaluation frameworks for quality latency and safety
- Develop model serving infrastructure
- Document model design decisions
- Implement RAG architectures
- Implement agentic LLM workflows
- Monitor model drift performance and data quality
- Set up experiment tracking and model registries
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Agentic LLM | Attention | Azure Machine Learning | CI/CD | Docker | Embeddings | Fine Tuning | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | JAX | Kubernetes | LLM Fine-tuning | Language Models | Large Language Models | LoRA | MLOps | MLflow | Machine Learning | Model Evaluation | NLP | NVIDIA Triton | PEFT | Prompt Chaining | Prompt engineering | PyTorch | Python | Quantization | RAG | RLHF | Text Generation | Text generation inference | Tokenization | Torchserve | VLLM | Vector Databases | Vertex AI | Weights and Biases
Education
N/A
Roles
AI | AI/ML Engineer | Engineer | ML Engineer | MLOps Engineer
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