中级机器学习工程师 - Databricks
Semi Senior Machine Learning Engineer - Databricks
🚀 加入我们的远程数据产品和机器学习开发初创公司！ 🚀
Mutt Data 是一家致力于使用前沿大数据和机器学习技术打造创新系统的动态初创公司。
我们正在寻找一名中级机器学习工程师，以帮助我们将专业知识提升到新的高度。如果你也像我们一样是数据爱好者，我们很期待与你联系！ 🐶🚀
这个机会是与位于墨西哥城的领先跨国饮料公司合作。你将参与对本地区关键客户有重大影响的数据和机器学习项目。
你将负责将机器学习解决方案工业化、部署、监控和扩展，确保在模型整个生命周期中遵循 MLOps 最佳实践，实现可追溯性、可靠性及运营卓越性。该职位与数据科学家、数据工程师和业务相关方紧密合作，在将 ML 模型转化为稳健的生产级系统方面发挥关键作用。在快节奏、协作的环境中，成功需要强大的技术主导能力、细致的关注以及对构建可靠 ML 平台的热情。
🚀 我们所做的
- 利用我们的专长，为需求规划和预算预测构建现代机器学习系统。
- 开发可扩展的数据基础设施，提升针对每个客户的高层决策能力。
- 提供全面的数据工程和定制 AI 解决方案，优化基于云的系统。
- 使用生成式 AI，帮助电商平台和零售商更快地创建更高质量的广告。
- 构建深度学习模型，增强各行业的视觉识别和自动化能力，提高产品分类、质量控制和信息检索效果。
- 开发推荐模型，为电商、流媒体和数字平台提供个性化用户体验，提升用户参与度和转化率。
🌟 我们的合作伙伴
- 亚马逊网络服务（AWS）
- Astronomer
- Databricks
🌟 我们的价值观
- 📊 我们是数据爱好者
- 🤗 我们是开放的团队合作者
- 🚀 我们承担责任
- 🌟 我们保持积极心态
🔍 对我们正在做什么感到好奇吗？查看我们的案例研究，并深入阅读我们的博客文章，了解更多关于我们的文化以及我们正在进行的令人兴奋的项目！ 🚀
职责 🤓
- 将机器学习模型工业化并部署到生产环境，进行扩展。
- 设计和维护端到端的训练、推理和重新训练管道。
查看英文原文
🚀 Join Our Data Products and Machine Learning Development Remote Startup! 🚀
Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies.
We’re looking for a Semi Senior Machine Learning Engineer to help take our expertise to the next level. If you consider yourself a data nerd like us, we’d love to connect! 🐶🚀
This opportunity is with a leading multinational beverage company based in Mexico City. You’ll be working on impactful data and machine learning initiatives for a key client in the region.
You'll be responsible for industrializing, deploying, monitoring, and scaling Machine Learning solutions in production, ensuring MLOps best practices, traceability, reliability, and operational excellence across the full model lifecycle. This role works closely with Data Scientists, Data Engineers, and business stakeholders, playing a key role in turning ML models into robust, production-grade systems. Strong technical ownership, attention to detail, and a passion for building reliable ML platforms are essential to succeed in this fast-paced, collaborative environment.
🚀 What We Do
- Leveraging our expertise, we build modern Machine Learning systems for demand planning and budget forecasting.
- Developing scalable data infrastructures, we enhance high-level decision-making, tailored to each client.
- Offering comprehensive Data Engineering and custom AI solutions, we optimize cloud-based systems.
- Using Generative AI, we help e-commerce platforms and retailers create higher-quality ads, faster.
- Building deep learning models, we enhance visual recognition and automation for various industries, improving product categorization, quality control, and information retrieval.
- Developing recommendation models, we personalize user experiences in e-commerce, streaming, and digital platforms, driving engagement and conversions.
🌟 Our Partnerships
- Amazon Web Services
- Astronomer
- Databricks
🌟 Our Values
- 📊 We are Data Nerds
- 🤗 We are Open Team Players
- 🚀 We Take Ownership
- 🌟 We Have a Positive Mindset
🔍 Curious about what we’re up to? Check out our case studies and dive into our blog post to learn more about our culture and the exciting projects we’re working on! 🚀
Responsibilities 🤓
- Industrialize, deploy, and scale Machine Learning models into production environments.
- Design and maintain training, inference, and retraining pipelines end-to-end.
- Build and maintain CI/CD pipelines for ML workflows, ensuring smooth and reliable releases. Implement and manage model tracking, versioning, and registry using MLflow.
- Develop and expose APIs for model serving, ensuring performance and scalability.
- Orchestrate workflows and jobs on Databricks (Workflows, Jobs, Repos).
- Containerize ML applications with Docker and support deployment on Kubernetes-based infrastructure. Implement model governance and versioning practices to ensure traceability across the ML lifecycle.
- Collaborate closely with Data Scientists, Data Engineers, and business stakeholders to align technical solutions with business needs.
- Promote MLOps best practices and modern ML architecture across the team.
Required Skills
- Advanced Python and SQL.
- Experience with Spark / PySpark.
- Solid experience with CI/CD pipelines and Git.
- Experience with MLflow (tracking, registry, and deployment).
- Experience with Docker and working knowledge of Kubernetes concepts.
- Experience with Azure Cloud.
- Experience implementing model monitoring and observability practices.
- Strong understanding of MLOps and ML architecture principles.
- Experience deploying models to production at scale.
Nice to Have Skills 😉
- Hands-on experience with Databricks (Workflows, Jobs, Repos).
- Experience with other cloud providers (AWS, GCP)
- Experience with Kubernetes in production environments.
🎁 Perks
- 🌍 Remote-first culture – work from anywhere!
- 🚀 In-Company English Lessons.
- 💪 Wellhub or sports club stipend to stay active
- 🚀 AWS, DBT, Google Cloud, Azure & Databricks certifications fully covered
- 🍕 Food credits via Pedidos Ya – because great work deserves great food.
- 🎂 Birthday off + an extra vacation week (Mutt Week! 🏖️)
- 🤝 Referral bonuses – help us grow the team & get rewarded!
- ✈️🏝️ Annual Mutters' Trip – an unforgettable getaway with the team!
- 👶 Monthly Childcare Reimbursement – Because supporting families matters too