Jr. Fullstack Gen AI Engineer
Tasks
- Apply LoRA
- Build transformer based architectures
- Deploy models with cloud tools
- Deploy with MLOps platforms
- Detect hallucinations
- Ensure fairness compliance
- Ensure privacy & compliance
- Ensure responsible AI compliance
- Ensure security compliance
- Evaluate foundation models
- Evaluate models
- Experiment with GANs
- Experiment with VAEs
- Experiment with diffusion models
- Explain model outputs
- Fine-tune large language models
- Implement LLMOps practices
- Implement model observability
- Implement prompt engineering
- Implement rollback strategies
- Manage model lifecycle
- Mentor AI/ML engineers
- Monitor prompt drift
- Optimize LLM performance
- Prototype GenAI capabilities
- Publish internal research
- Translate business problems into AI solutions
- Use PEFT
- Use reinforcement learning RLHF
- Use transfer learning
- Version models
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Azure | CI/CD | Containerization | Diffusion Models | Docker | Embeddings | Explainable AI | Faiss | FastAPI | Flask | GAN | GCP | Hallucination detection | Hugging Face | Hugging Face Transformers | Kubernetes | LLMOps | Langchain | Langgraph | Language Models | Large Language Models | LoRA | MLOps | Microservices | Model Evaluation | Model versioning | Observability | PEFT | Pinecone | Prompt Drift | Prompt engineering | PyTorch | Python | RLHF | Reinforcement Learning | Responsible AI | Semantic Search | TensorFlow | Transfer Learning | Transformers | VAE | Vector Databases | Weaviate
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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