Kaizen Analytix LLC is seeking an AI Engineer to design, develop, and maintain complex AI projects and managed data warehouses, focusing on deep learning, vector embeddings, and handling massive unstructured datasets for AI/ML solutions and actionable business insights.
Requirements
- Demonstrable experience working with Generative AI and Large Language Models (e.g., GPT variants, Llama, Mistral, Gemini) including fine-tuning, RAG, and prompt engineering.
- Strong proficiency in Python and common AI/ML libraries/frameworks (e.g., TensorFlow, PyTorch, Keras, Scikit-learn, Hugging Face Transformers, LangChain).
- Solid understanding of core deep learning concepts, model architectures, training methodologies, and evaluation metrics.
- Experience designing scalable, reliable AI/ML system architectures.
- Familiarity with cloud platforms (AWS, Azure, or GCP) and their respective AI/ML services (e.g., SageMaker, Azure ML, Azure AI Foundry, GCP Vertex AI, GCP AI Studio).
- Understanding of AIOps principles and common use cases (experience implementing AIOps solutions is a strong plus).
- Solid software engineering fundamentals (data structures, algorithms, code quality, testing, version control with Git).
Responsibilities
- Design, build, fine-tune, and deploy generative models and LLMs for various enterprise applications (e.g., content generation, chatbots, code assistance, data analysis).
- Leverage your deep knowledge of transformer architectures (e.g., GPT, BERT, T5) to fine-tune, optimize, and deploy Large Language Models (LLMs) for specific tasks.
- Implement state-of-the-art techniques such as Agentic AI, Context Engineering - Retrieval-Augmented Generation (RAG), prompt engineering, and model quantization.
- Build, train, and deploy autonomous and semi-autonomous AI agents capable of complex reasoning, tool use, and decision-making.
- Develop and implement AI/ML models for AIOps use cases, including anomaly detection, predictive monitoring, root cause analysis, and automated remediation.
- Write clean, efficient, well-documented, and production-ready code (primarily Python).
- Build and maintain data pipelines for training, evaluating, and serving AI models.
Other
- Proven industry experience (typically 3-5+ years, adjust as needed) as an AI/ML Engineer, with hands-on experience building and deploying machine learning models in production.
- Excellent analytical, problem-solving, and critical-thinking skills.
- Strong communication and collaboration skills, with the ability to explain complex technical concepts to diverse audiences.
- Experience working in an agile development environment.
- This is a remote role.
