AI/ML Developer
Tasks
- Build RAG solutions
- Build model registries and experiment tracking
- Conduct reinforcement learning from human feedback experiments
- Conduct supervised fine tuning experiments
- Curate and preprocess datasets
- Define model evaluation frameworks
- Deploy models with Docker and Kubernetes
- Design train fine tune small language models
- Develop model cards and documentation
- Implement automated retraining triggers
- Implement distributed training pipelines
- Monitor model drift and data drift
- Optimize model inference performance
- Perform hyperparameter optimization and ablation studies
- Prototype and validate nlp llm research techniques
- Run red teaming bias and safety evaluations
Perks/Benefits
- N/A
Skills/Tech-stack
AWS SageMaker | Accelerate | Adapter Layers | Apache Spark | Azure Machine Learning | C++ | CI/CD | CUDA | Comet | Dask | DeepSpeed ZeRO | Docker | FSDP | Faiss | GPU Training | Git | GitHub | GitLab | Google Cloud | Google Cloud Vertex | Google Cloud Vertex AI | Hugging Face | Hugging Face Datasets | Hugging Face Transformers | JAX | Knowledge Distillation | Kubernetes | Language Models | Large Language Models | LoRA | MLflow | MOE | Machine Learning | Mixture of Experts | Multi-GPU | Multi-GPU Training | NumPy | ONNX | PEFT | Pandas | Pinecone | Pruning | PyTorch | Python | QLoRA | Quantization | RAG | Red Teaming | TRL | TensorFlow | TensorRT | Vector Databases | Vertex AI | Weaviate
Education
N/A
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer | NLP Engineer
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