5 Maganti It Resource Jobs
Machine Learning Engineer - LLM Models (5-10 yrs)
Maganti It Resource
posted 5d ago
Flexible timing
Key skills for the job
Job Overview :
We are seeking a 4+ years of highly skilled LLM Engineer with expertise in working across various Large Language Model (LLM) engines to design, develop, and deploy cutting-edge AI-powered products.
The ideal candidate is passionate about LLMs, generative AI, and NLP and has hands-on experience in fine-tuning, optimizing, and integrating LLMs into scalable applications.
Key Responsibilities :
- LLM Model Selection & Optimization.
- Work with different LLM engines (GPT, LLaMA, Mistral, Claude, Gemini, etc.) to select the best fit for specific use cases.
- Fine-tune and optimize models for performance, efficiency, and cost-effectiveness.
- Implement prompt engineering, RAG (Retrieval-Augmented Generation), and memory-based techniques for enhanced outputs.
- AI Product Development.
- Design and develop LLM-powered applications, such as AI-driven assistants, chatbots, document automation, and search engines.
- Build scalable and innovative AI solutions that leverage multimodal models (text, voice, vision).
- Work on AI personalization strategies using embeddings, vector search, and advanced NLP pipelines.
- Integration & Deployment.
- Deploy LLMs using cloud platforms (AWS, Azure OpenAI, GCP Vertex AI) and MLOps frameworks (Hugging Face, LangChain, Ray).
- Implement model monitoring, logging, and bias detection mechanisms to ensure accuracy, fairness, and security.
- Work with APIs and microservices to integrate AI solutions into enterprise applications.
- Research & Innovation.
- Stay up to date with the latest advancements in LLMs, NLP, and generative AI.
- Experiment with new architectures and hybrid AI models to push the boundaries of AI innovation.
- Collaborate with cross-functional teams (Product, Engineering, Data Science) to drive AI-powered product enhancements.
Required Skills & Qualifications :
- Strong expertise in Python, TensorFlow, PyTorch, and JAX.
- Hands-on experience with LLM APIs & Open-Source Models (OpenAI, Hugging Face, Cohere, Mistral, etc.
- Deep understanding of transformer models, embeddings, tokenization, and fine-tuning techniques.
- Experience with RAG pipelines, vector databases (FAISS, Pinecone, Weaviate), and prompt tuning.
- Knowledge of cloud-based AI model deployment (AWS SageMaker, Azure ML, GCP Vertex AI).
- Familiarity with ethical AI, bias mitigation, and hallucination control in LLM applications.
Preferred Qualifications :
- Experience in building LLM-powered SaaS or enterprise products.
- Background in Reinforcement Learning (RLHF) and few-shot learning.
- Knowledge of multimodal AI (text, image, and voice models).
- Exposure to AI security, compliance, and governance frameworks.
Functional Areas: Other
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