Machine Learning Engineer

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Category: Technology Location: We are looking for a highly skilled Machine Learning Engineer to join our AI and data science team. In this role, you will design, develop, and deploy machine learning models and pipelines that power critical data-driven solutions across our organization. You’ll collaborate with data scientists, software engineers, and product teams to deliver intelligent systems at scale. Responsibilities Design and implement machine learning models for classification, regression, recommendation, NLP, or time-series forecasting tasks. Develop, test, and maintain scalable ML pipelines for training, validation, and inference. Collaborate with data engineers to build efficient data ingestion and feature extraction systems. Optimize model performance using techniques like hyperparameter tuning, cross-validation, and regularization. Deploy models to production using MLOps practices with tools like MLflow, TFX, or SageMaker. Monitor and maintain the health of deployed models, updating them as needed. Document ML experiments, metrics, and decisions. Work closely with cross-functional teams to identify machine learning opportunities and define technical solutions. Requirements Bachelor’s or Master’s in Computer Science, Machine Learning, Data Science, or related field (Ph.D. a plus). 3–5+ years of hands-on experience building machine learning models in production. Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch. Experience with ML pipeline tools (e.g., Airflow, Kubeflow, MLflow). Familiarity with cloud services (AWS, GCP, or Azure) and model deployment. Solid understanding of statistics, data structures, and algorithms. Experience with version control (Git), containerization (Docker), and CI/CD for ML. Preferred Qualifications Experience with NLP or computer vision projects. Familiarity with big data tools (e.g., Spark, Hadoop). Experience using GPU-accelerated training environments. Details Originally posted on Himalayas

类别：技术 地点：我们正在寻找一名高技能机器学习工程师加入我们的AI和数据科学团队。在这个角色中，您将设计、开发和部署机器学习模型和流水线，为我们组织内关键的数据驱动解决方案提供支持。您将与数据科学家、软件工程师和产品团队合作，大规模交付智能系统。 职责 为分类、回归、推荐、NLP或时间序列预测任务设计和实现机器学习模型。 开发、测试和维护可扩展的ML流水线，用于训练、验证和推理。 与数据工程师合作，构建高效的数据摄取和特征提取系统。 使用超参数调优、交叉验证和正则化等技术优化模型性能。 使用MLOps实践和MLflow、TFX或SageMaker等工具将模型部署到生产环境。 监控和维护已部署模型的健康状态，并在需要时进行更新。 记录ML实验、指标和决策。 与跨职能团队密切合作，识别机器学习机会并定义技术解决方案。 要求 计算机科学、机器学习、数据科学或相关领域的学士或硕士学位（博士学位为加分项）。 3–5年以上在生产环境中构建机器学习模型的实践经验。 熟练掌握Python和ML框架，如scikit-learn、TensorFlow或PyTorch。 具有ML流水线工具经验（例如Airflow、Kubeflow、MLflow）。 熟悉云服务（AWS、GCP或Azure）和模型部署。 对统计学、数据结构和算法有扎实理解。 具有版本控制（Git）、容器化（Docker）和ML的CI/CD经验。 优先资格 具有NLP或计算机视觉项目经验。 熟悉大数据工具（例如Spark、Hadoop）。 具有使用GPU加速训练环境的经验。 详情 最初发布于Himalayas

⚑ 岗位信息收录自公开招聘页（Himalayas），以雇主官网为准