Info Way Solutions
Gen AI/ML Engineer
Info Way Solutions - Austin, Texas, us, 78716
Work at Info Way Solutions
Overview
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Overview
Gen AI/ML Engineer
Location: Austin, TX- (Onsite)
Type : Contract
Job Requirement: Key Responsibilities: Design, develop, and deploy AI/ML models, with a focus on Generative AI and autonomous agents. Implement LLM-based AI agents, fine-tune pre-trained models, and integrate them into applications. Develop and optimize multi-modal AI systems (text, image, audio, video) using state-of-the-art techniques. Work with Reinforcement Learning (RL), Prompt Engineering, and Knowledge Graphs to improve AI agent capabilities. Collaborate with cross-functional teams to integrate AI-powered solutions into products and services. Conduct research, experiment with emerging AI frameworks, and optimize model performance. Ensure scalability, efficiency, and ethical considerations in AI solutions. Required Skills & Qualifications:
Bachelor's, Master's, or Ph.D. in Computer Science, AI, Data Science, or a related field. 3+ years of experience in AI/ML development, with expertise in Generative AI and AI agents. Proficiency in Python, TensorFlow/PyTorch, and Hugging Face Transformers. Experience with LLMs (GPT, Claude, Gemini, etc.), vector databases, and retrieval-augmented generation (RAG). Strong understanding of NLP, deep learning, and model fine-tuning techniques. Experience working with MLOps, cloud-based AI deployment (AWS/GCP/Azure), and containerization (Docker, Kubernetes). Knowledge of prompt engineering, reinforcement learning, and AI safety principles. Strong problem-solving skills, ability to work independently and collaboratively.
Preferred Qualifications:
Experience with self-learning AI agents, autonomous workflows, or multi-agent systems. Background in graph-based AI, symbolic reasoning, or cognitive architectures. Contributions to open-source AI/ML projects or research publications in relevant domains.
Job Requirement: Key Responsibilities: Design, develop, and deploy AI/ML models, with a focus on Generative AI and autonomous agents. Implement LLM-based AI agents, fine-tune pre-trained models, and integrate them into applications. Develop and optimize multi-modal AI systems (text, image, audio, video) using state-of-the-art techniques. Work with Reinforcement Learning (RL), Prompt Engineering, and Knowledge Graphs to improve AI agent capabilities. Collaborate with cross-functional teams to integrate AI-powered solutions into products and services. Conduct research, experiment with emerging AI frameworks, and optimize model performance. Ensure scalability, efficiency, and ethical considerations in AI solutions. Required Skills & Qualifications:
Bachelor's, Master's, or Ph.D. in Computer Science, AI, Data Science, or a related field. 3+ years of experience in AI/ML development, with expertise in Generative AI and AI agents. Proficiency in Python, TensorFlow/PyTorch, and Hugging Face Transformers. Experience with LLMs (GPT, Claude, Gemini, etc.), vector databases, and retrieval-augmented generation (RAG). Strong understanding of NLP, deep learning, and model fine-tuning techniques. Experience working with MLOps, cloud-based AI deployment (AWS/GCP/Azure), and containerization (Docker, Kubernetes). Knowledge of prompt engineering, reinforcement learning, and AI safety principles. Strong problem-solving skills, ability to work independently and collaboratively.
Preferred Qualifications:
Experience with self-learning AI agents, autonomous workflows, or multi-agent systems. Background in graph-based AI, symbolic reasoning, or cognitive architectures. Contributions to open-source AI/ML projects or research publications in relevant domains.