
Machine Learning Engineer
3 weeks ago
Job Description
Build autonomous AI-driven agents for tasks such as reasoning, decision-making, automation, and contextual understanding.
Customize and deploy GPT, LLaMA, Claude, Mistral, and other foundation models to solve industry-specific challenges.
Design scalable, production-ready AI workflows using Python, LangChain, LlamaIndex, OpenAI functions, and AutoGPT.
Enhance AI agents with retrieval-augmented generation (RAG), vector databases (FAISS, Pinecone, Weaviate, ChromaDB), and knowledge graphs.
Work with text, images, audio, and structured data to create multimodal AI applications.
Implement reinforcement learning, agentic workflows, and action-planning techniques to enhance AI autonomy.
Optimize and deploy models on cloud platforms (AWS, Azure, GCP) and ensure efficiency in a microservices-based architecture.
Leverage few-shot learning, prompt chaining, and tool-use APIs to improve AI reasoning capabilities.
Develop responsible AI solutions by addressing bias, explainability, and security concerns.
Proven experience developing GenAI-powered applications and AI agents.
Strong proficiency in Python and AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, LlamaIndex, OpenAI API).
Hands-on expertise in LLM fine-tuning, model adaptation, and prompt engineering.
Familiarity with vector databases (FAISS, Pinecone, Weaviate, ChromaDB) and knowledge retrieval techniques.
Experience integrating AI with APIs, automation frameworks, and microservices.
Working knowledge of cloud-based AI deployment (AWS, Azure, GCP).
Understanding of NLP, reinforcement learning, and multi-agent architectures.
Strong problem-solving skills, ability to work independently, and in a collaborative team environment.
Excellent communication skills with a passion for AI-driven innovation.
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