AI Engineer

Company Description Bytezera is a data services provider that specialise in AI and data solutions to help businesses maximise their data potential. With expertise in data-driven solution design, machine learning, AI, data engineering, and analytics, we empower organizations to make informed decisions and drive innovation. Our focus is on using data to achieve competitive advantage and transformation. About the Role We are seeking a highly skilled and hands-on AI Engineer to drive the development of cutting-edge AI applications using the latest in Large Language Models (LLMs) , agentic frameworks , and Generative AI technologies . This role covers the full AI development lifecycle—from data preparation and model training to deployment and optimization—with a strong focus on NLP and open-source foundation models . You will be directly involved in building and deploying goal-driven, autonomous AI agents and scalable AI systems for real-world use cases. Key Responsibilities Build and deploy advanced LLM-based AI agents using frameworks such as LangGraph , CrewAI , AutoGen , and OpenAgents . Fine-tune and optimize open-source LLMs (e.g., GPT-4 , LLaMA 3 , Mistral , T5 ) for domain-specific applications. Design and implement retrieval-augmented generation (RAG) pipelines with vector databases like FAISS , Weaviate , or Pinecone . Develop NLP pipelines using Hugging Face Transformers , spaCy , and LangChain for various text understanding and generation tasks. Leverage Python with PyTorch and TensorFlow for training, fine-tuning, and evaluating models. Prepare and manage high-quality datasets for model training and evaluation. Deploy AI models in cloud-native production environments using AWS services (e.g., SageMaker, Lambda, Bedrock). Containerize and orchestrate deployments with Docker and Kubernetes . Continuously monitor model performance and improve accuracy, efficiency, and scalability. Collaborate with cross-functional teams to ensure seamless integration and delivery of AI capabilities. Experience & Qualifications 2+ years of hands-on experience in AI engineering , machine learning , or data science roles. Proven track record in building and deploying NLP or Generative AI models. Experience with agentic workflows or autonomous AI agents is highly desirable. Technical Skills Languages & Libraries:Python, PyTorch, TensorFlow, Hugging Face Transformers, LangChain, spaCy LLMs & Generative AI:GPT, LLaMA 3, Mistral, T5, Claude, and other open-source or commercial models Agentic Tooling:LangGraph, CrewAI, AutoGen, OpenAgents Vector databases (Pinecone or ChromaDB) DevOps & Deployment: Docker, Kubernetes, AWS (SageMaker, Lambda, Bedrock, S3) Core ML Skills: Data preprocessing, feature engineering, model evaluation, and optimization Qualifications:Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, or a related field. Show more Show less