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职位简介 负责开发、优化及部署AI模型，包括模型训练、微调、数据处理及性能优化。您将与跨部门团队合作，打造高效、可扩展的AI解决方案，并持续提升模型表现与业务价值。 岗位职责 · 开发、训练及优化AI / Machine Learning模型 · 处理、清洗及管理大型数据集 · 调试AI模型并优化模型性能 · 监控模型表现并持续改善准确率及效率 · 与产品、软件及数据团队合作开发AI解决方案 · 整理技术文件及开发流程 任职要求 · 3年以上AI / Machine Learning相关经验 · 熟练使用Python · 熟悉TensorFlow、PyTorch、Scikit-learn、Hugging Face等AI框架 · 具备数据处理及模型训练经验 · 熟悉Machine Learning、Deep Learning及LLM相关技术 · 具备良好的分析能力、问题解决能力及团队合作精神 加分项 · 有RAG（Retrieval-Augmented Generation）开发经验 · 有AI模型部署及生产环境维护经验 · 熟悉Apache Spark或大型数据处理 · 硕士或以上学历（AI、Computer Science、Data Science等相关科系） 加入我们 | Why Join Us · 参与AI产品研发及大型AI项目 · 接触最新AI技术（LLM、RAG、Machine Learning） · 与经验丰富的AI及工程团队合作 · 提供良好的职业发展与学习机会 Job Summary Develop, fine-tune, and optimize AI models with a focus on machine learning, dataset processing, and model performance. Work closely with cross-functional teams to build scalable AI solutions and deliver innovative products that create real business impact. Key Responsibilities · Develop, train, and optimize AI/Machine Learning models · Process, clean, and manage large-scale datasets · Debug AI models and improve model performance · Monitor production models and optimize accuracy, scalability, and efficiency · Collaborate with software engineers, data scientists, and product teams · Document AI development processes and best practices Requirements · 3+ years of experience in AI/Machine Learning development · Strong proficiency in Python · Experience with TensorFlow, PyTorch, Scikit-learn, Hugging Face, or similar AI frameworks · Strong understanding of Machine Learning, Deep Learning, and AI model training · Experience with dataset processing and model optimization · Excellent analytical, problem-solving, and communication skills Nice to Have · Experience with RAG (Retrieval-Augmented Generation) systems · Experience deploying AI models to production environments · Knowledge of Apache Spark or large-scale data processing · Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field Why Join Us · Work on cutting-edge AI and Machine Learning projects · Gain hands-on experience with LLMs, RAG, and modern AI technologies · Collaborate with an experienced AI and engineering team · Excellent opportunities for career growth and continuous learning
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.