全职 Prompt Engineer - AI Engineer - AI-ML Engineer 工作, 薪水, Project Human Resource 公司招聘中 - Ricebowl

We are looking for a highly motivated Prompt Engineer / AI Engineer / AI/ML Engineer to contribute to the design, development, and optimization of intelligent AI-powered solutions. In this role, you will work on cutting-edge artificial intelligence technologies, including large language models (LLMs), machine learning algorithms, natural language processing (NLP), and automation systems. You will collaborate with cross-functional teams to build scalable AI applications that improve business processes, enhance user experiences, and support data-driven decision-making.

You will design, refine, and evaluate prompts for generative AI models to maximize response quality, accuracy, consistency, and efficiency across different use cases. You will develop AI workflows, integrate AI models into software applications through APIs and cloud services, and optimize system performance using advanced engineering techniques.

The role involves building, training, fine-tuning, testing, and deploying machine learning models for various business applications. You will preprocess structured and unstructured datasets, perform feature engineering, analyze model performance, and continuously improve prediction accuracy using appropriate evaluation metrics.

You will participate in the entire AI development lifecycle, from problem definition and data preparation to model deployment, monitoring, maintenance, and continuous optimization. Responsibilities also include implementing retrieval-augmented generation (RAG) pipelines, vector databases, embeddings, AI agents, and workflow automation where appropriate.

You will conduct research on emerging AI technologies, evaluate new tools, frameworks, and open-source models, and recommend innovative solutions that align with organizational objectives. You will document technical processes, maintain coding standards, and contribute to reusable AI components that improve development efficiency.

The role also requires close collaboration with software engineers, product managers, designers, and business stakeholders to translate business requirements into practical AI solutions. You will troubleshoot technical issues, optimize model latency, improve inference efficiency, and ensure AI systems remain reliable, scalable, and secure.

You will support responsible AI development by considering model safety, fairness, transparency, and privacy throughout the development process. Continuous learning, experimentation, and knowledge sharing are encouraged to keep pace with the rapidly evolving AI landscape.

• Strong understanding of artificial intelligence, machine learning, deep learning, and natural language processing concepts.
• Proficiency in Python and familiarity with AI development libraries and frameworks.
• Knowledge of large language models (LLMs), prompt engineering techniques, retrieval-augmented generation (RAG), embeddings, and vector databases.
• Familiarity with machine learning workflows, including data preprocessing, model training, evaluation, validation, and deployment.
• Understanding of supervised, unsupervised, reinforcement, and generative AI methodologies.
• Ability to integrate AI services using APIs, cloud platforms, and modern software architectures.
• Knowledge of data structures, algorithms, software engineering principles, and version control systems.
• Familiarity with deep learning frameworks such as TensorFlow, PyTorch, or similar technologies.
• Understanding of SQL, NoSQL databases, data pipelines, and ETL processes.
• Ability to analyze complex datasets and convert insights into practical AI solutions.
• Knowledge of AI model optimization, inference performance, monitoring, and scalability best practices.
• Understanding of MLOps concepts, CI/CD pipelines, containerization, and deployment workflows is advantageous.
• Familiarity with cloud computing platforms and AI infrastructure services.
• Strong analytical thinking, problem-solving, and debugging skills.
• Excellent communication and collaboration skills with both technical and non-technical stakeholders.
• Ability to write clean, maintainable, and well-documented code.
• Strong organizational skills with the ability to manage multiple projects and priorities.
• Passion for emerging AI technologies and continuous professional learning.
• Commitment to ethical AI practices, responsible model development, data privacy, and security standards.