AI Software Engineer

<p>Duties:</p><p>·Acquire, preprocess, and engineer features from diverse data sources.</p><p>·Design and maintain robust data pipelines while ensuring adherence to data governance standards.</p><p>·Explore, develop, and test machine learning and deep learning algorithms.</p><p>·Adapt commercial or open-source AI platforms and frameworks (e.g., Azure ML, AWS ML, Hugging Face, Deepseek, etc.) to meet organizational needs.</p><p>·Conduct thorough model validation, fine-tuning, and bias/error assessments.</p><p>·Partner with other technical teams to containerize models, expose APIs, and embed AI capabilities into HPC cloud platform using CI/CD methodologies.</p><p>·Set up monitoring tools to assess model accuracy, drift, and system performance.</p><p>·Continuously enhance models to ensure optimal performance and compliance with internal policies.</p><p>·Produce clear technical documentation and lead training sessions to empower business teams in using AI tools effectively.</p><p>·Help define best practices and contribute to internal AI guidelines and frameworks.</p><p>·Keep pace with emerging AI research and industry innovations.</p><p>·Experiment with advanced AI techniques and recommend adoption when they offer measurable business impact.</p><p>·Perform other duties assigned by supervisor.</p><p></p><p>Qualifications:</p><p>·Bachelor’s degree or higher in Computer Science, Information Technology, Artificial Intelligence, Fintech, or related fields.</p><p>·At least 3 years of practical experience in AI engineering, machine learning, or data science, ideally in corporate environments.</p><p>·Demonstrated portfolio of deployed AI models (e.g., GitHub repositories, project summaries, etc.).</p><p>·Hands-on experience with AI models and techniques (e.g. LMM, RAG, Agentic, transformer, RNN, LSTM, etc.)</p><p>·Skilled in Python, with hands-on experience using ML libraries (TensorFlow, PyTorch, scikit-learn), SQL, and cloud-based AI/ML platforms (AWS, Azure, GCP); familiarity with MLOps tools such as Docker, Kubernetes, MLflow.</p><p>·Strong proficiency in popular deep learning frameworks (e.g., TensorFlow, PyTorch, MXNet) and GPU-acceleratedprogramming (e.g., CUDA, cuDNN).</p><p>·Strong analytical mindset with solid grounding in statistics, data ethics, and governance principles.</p><p>·Excellent communication skills with the ability to distill technical concepts into actionable business insights.</p><p>·Proficient in both English and Chinese.</p><p><strong>Job Responsibilities:</strong></p><p>·Responsible for multi-source data collection, cleaning, pre-processing, and feature engineering</p><p>·Design and maintain a highly reliable data pipeline, strictly following data governance standards</p><p>·Develop and test machine learning and deep learning algorithms</p><p>·Deeply customize business or open-source AI platforms (such as Azure ML, AWS SageMaker, Hugging Face, Deepseek, etc.), meeting enterprise-level needs</p><p>·Execute model validation, fine-tuning, bias and error analysis</p><p>·Collaborate with backend and cloud computing teams, complete model containerization, API packaging, and integration into the HPC cloud platform through CI/CD pipelines</p><p>·Establish model accuracy, drift, and system performance monitoring mechanisms</p><p>·Continuously iterate and optimize the model to ensure performance and compliance are both optimized</p><p>·Write high-quality technical documentation and provide AI tool training to business teams</p><p>·Participate in the development of internal AI best practices and governance frameworks</p><p>·Stay up to date with global AI frontier research, evaluate and introduce innovative technologies with commercial value</p><p>·Execute other tasks assigned by the superior</p><p><strong>Requirements:</strong></p><p>·Computer Science, Artificial Intelligence, Fintech or related professional bachelor's degree or above</p><p></p><p>·Have a showcase of already deployed AI models (GitHub, project reports, etc.)</p><p>· Proficient in LMM, RAG, Agentic, Transformer, RNN, LSTM, etc., cutting-edge technologies</p><p>· Proficient in Python, familiar with TensorFlow, PyTorch, scikit-learn, etc. frameworks, with SQL and mainstream cloud AI platform practical experience</p><p>·Familiar with the MLOps full process tool chain (Docker, Kubernetes, MLflow, etc.)</p><p>·Have GPU acceleration programming experience (CUDA, cuDNN)</p><p>·Good statistical foundation, deep understanding of data ethics and governance principles</p><p>·Excellent technical communication skills, able to translate complex concepts into business insights</p><p>·Proficient in both Chinese and English</p>