Staff Machine Learning Engineer, Coinbase

• 8+ years of experience in machine learning and software engineering
• Proven expertise in designing, building, scaling, and maintaining production services, with a strong focus on data processing/machine learning/analytics
• Hands-on experience with at least one ML model type, such as LLMs, GNNs, Deep Learning, Logistic Regression, or Gradient Boosting Trees
• Proficiency in one or more areas, including data mining, information retrieval, advanced statistics, natural language processing, or computer vision
• Ability to write high-quality, well-tested code that effectively addresses customer needs
• Experience mentoring and developing junior engineers by implementing processes and setting a high standard for excellence
• Passion for building an open financial system that connects the world
• Exceptional written and verbal communication skills, with a commitment to open and transparent cultural practices

Desirable

• As a Machine Learning Engineer on our team, you will play a key role in this transformation, utilizing state-of-the-art AI models, frameworks, and tools, along with diverse and extensive data sources, including blockchain data
• Your work will focus on breaking down barriers to cryptocurrency adoption and shaping the future of AI-powered customer interactions
• Explore and apply advanced machine learning techniques, including large language models (LLMs) and deep learning, to solve complex challenges across the organization
• Collaborate with management and stakeholders to define strategic roadmaps and translate them into actionable quarterly plans
• Drive project execution by managing priorities, deadlines, and deliverables, leveraging your technical expertise
• Develop high-quality, well-tested Python code to address critical product and business needs
• Design scalable, secure systems using state-of-the-art AI/ML technologies and industry best practices
• Mentor team members on design principles, coding standards, and the adoption of AI productivity tools
• Troubleshoot and resolve complex technical issues to improve system reliability, scalability, and operational efficiency
• Ensure the security, scalability, and architectural integrity of feature designs through thorough reviews across teams