Machine Learning Engineer

Block is organized into business groups, each with dedicated product and engineering teams. Our team plays a vital role in supporting these groups by delivering AI-powered solutions that directly benefit our customers and drive business growth. We focus on the customer support space, where we build AI systems that make support experiences faster, more reliable, and more human-centered. The tools we create help automate support workflows, augment advocates with intelligent assistance, and ultimately improve the way millions of customers get help.

We are looking for an enthusiastic and experienced Machine Learning Engineer to join our team to build AI products. In this role, you will collaborate closely with teams across Block to understand their challenges and opportunities. You'll have the opportunity to work across the full development stack and set product strategy. You'll design, develop, and launch AI-driven tools and applications that address real customer needs, working in an environment that values creativity, experimentation, and practical problem solving.

You will partner with stakeholders to deliver highly visible solutions, staying at the forefront of AI advancements to ensure our products remain innovative and effective. We welcome individuals who are passionate about building for the real world, embracing pragmatic approaches, and seeing challenges from fresh, nontraditional viewpoints.

You Will

1. Leverage AI to automate workflows and deliver new AI-powered product experiences
2. Develop scalable AI systems and platforms
3. Collaborate across diverse teams to develop AI solutions by understanding and generalizing the problems of cross-functional stakeholders
4. Drive architectural decisions, system reliability improvements, and infrastructure automation
5. Mentor and guide other engineers
6. Champion engineering excellence through code reviews, technical documentation, and continuous improvement

You Have

1. 5+ years of experience in training and deploying ML models, developing ML software, and shipping customer-facing ML products.
2. Deep understanding of modern ML techniques including Large Language Model Agents and the ML lifecycle: from data collection and training to evaluation, prompting, context management, reasoning, safety evaluation and benchmarking, and deploying models into production.
3. A desire to understand our clients' needs in order to design tools and systems that solve our customer's problems. As a platform team, our main customers are internal developers and products.
4. Ability to produce production-quality code and services incorporating testing, evaluation, monitoring as well as the ability to quickly adapt to a new domain, hack MVP's, and iterate to improve product.
5. Strong communication skills (verbal and written) with technical and non-technical stakeholders.