> Markdown version of [/jobs/ext/4616595-machine-learning-engineer-systems-risk-and-trust](https://www.wearedevelopers.com/jobs/ext/4616595-machine-learning-engineer-systems-risk-and-trust). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Machine Learning Engineer (Systems), Risk and Trust

- **Company:** Block, Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Code Review, Data Cleansing, Data Structures, Python (Programming Language), Machine Learning, Object-Oriented Software Development, Tensorflow, Azure Machine Learning, Software Construction, Software Engineering, Cloud Platform System, Feature Engineering, Graph Neural Networks, Pytorch, Uncertainty Quantification (UQ), Deep Learning, Build Management, Scikit Learn, Machine Learning Operations, Software Version Control, Software Library, Docker
- **Published:** November 7, 2026
- **Apply:** https://www.juju.com/job/28_25303_0a4fd5e07d476c7361bf62f4fef4a2bc

## About the Role

* 5+ years of experience in designing and building deep learning capable ML pipelines and infrastructure
 * 8+ years of experience building software platforms
 * Proficiency in Python and experience with machine learning libraries, such as scikit-learn, TensorFlow, or PyTorch
 * Strong software engineering skills, including knowledge of data structures, algorithms, and object-oriented programming principles
 * Experience with cloud-based infrastructure and services, such as AWS, GCP, or Azure, and related machine learning tools and services
 * Familiarity with containerization and orchestration technologies, such as Docker and Kubernetes
 * Experience in dealing with sensitive/private data, both structured and unstructured
 * Experience with advanced techniques like irregular sequence modeling, uncertainty quantification, graph neural networks, homomorphic encryption, active learning systems, is a big plus
 * Strong problem-solving, analytical, and critical thinking skills
 * Entrepreneurial and have demonstrated ability to handle ambiguity
 * Excellent problem-solving, analytical, and communication skills

## Description

TBD's Risk and Trust team is on the mission to build world-class risk and trust management services to enable a truly open and decentralized financial ecosystem. We are looking for a skilled Machine Learning Engineer to help create and maintain our model development infrastructure. The ideal candidate will have a strong background in machine learning, software engineering, and cloud-based infrastructure, and will be responsible for designing, building, and optimizing the tools and systems that enable our team to develop, test, and deploy state-of-the-art machine learning models efficiently and effectively to further our mission of economic empowerment globally and solve real world problems with decentralized financial products., * Collaborate with machine learning modelers and other stakeholders to design and build a robust, scalable, and user-friendly model development infrastructure

 * Implement and maintain machine learning pipelines, including data preprocessing, feature engineering, model training, validation, and deployment
 * Integrate machine learning models with production systems, ensuring seamless and efficient model deployment and monitoring
 * Develop and maintain tools and libraries to facilitate rapid experimentation, model development, and evaluation for the machine learning team
 * Implement best practices for version control, code review, testing, and documentation, fostering a culture of high-quality software development
 * Stay current with the latest tools, technologies, and best practices in machine learning engineering and cloud-based infrastructure, and drive continuous improvement within the team
 * Monitor, troubleshoot, and optimize the performance of machine learning models and related infrastructure