Job 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.

You Will:

• 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

Qualifications

You Have:

• 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