Research Engineer

Description:

Block is one company built from many blocks, all united by the same purpose of economic empowerment. The blocks that form our foundational teams — People, Finance, Counsel, Hardware, Information Security, Platform Infrastructure Engineering, and more — provide support and guidance at the corporate level. They work across business groups and around the globe, spanning time zones and disciplines to develop inclusive People policies, forecast finances, give legal counsel, safeguard systems, nurture new initiatives, and more. Every challenge creates possibilities, and we need different perspectives to see them all. Bring yours to Block.

The Role

Since Block's inception, our innovative and technology-forward approach to risk management and customer protection has been fundamental to how we invent and build financial products. The Risk team at Block continues this legacy through a sophisticated, technology and science-led approach to protecting our customers and their funds. Our interdisciplinary structure combines Product Development, Science teams (specializing in modeling, analytics, and data science), Operations and key partners including Legal, Compliance and Policy, all working in concert to identify, assess, and solve complex risk challenges across access, fraud prevention and compliance.

This role is part of our Risk Labs team - this team’s mission is aimed at developing advanced deep learning and reinforcement learning based signals and learned representations for machine learning models. In this role, you’ll explore, develop and implement alternatives to traditional feature based ML with state-of-the-art models for solving risk problems. This team works across a wide-swath of the Risk organization touching a variety of use cases and collaborating with a diverse set of teams.

What You'll Be Up To
 

• Dreaming up, designing, and running big experiments to quickly test out cool (and practical) ideas
• Applying the latest theoretical breakthroughs to make our products even better
• Building experiments, prototypes, and architectural designs across computer science fields like ML, data mining, NLP, and agentic AI
• Contributing to the growth of new initiatives by sharing emerging trends and best practices, fostering a collaborative and innovative environment
• Taking the lead on defining data structures, frameworks, designs, and evaluation metrics for your research solutions – you'll have a lot of autonomy here
• Teaming up with folks inside the company to find new research areas and shape our long-term strategies
• Running experiments for your applied research, using simulations and prototypes to see what happens
• Refining how we do applied research, solidifying your hypotheses, and helping evolve our practices with minimal hand-holding
   

We’re Targeting
 

• A Level 6 hire, which usually means something like:

• BSc with 7-10 years experience
• MSc with 5-8 years experience
• PhD with 3-5 years experience
• End-to-end experience across the full ML lifecycle, from problem framing and data gathering to training, evaluation, deployment, and ongoing iteration
• Strong background in building and productionizing deep learning or advanced ML models using large-scale datasets
• Proficiency in designing and maintaining scalable ML pipelines, production services, and high-quality ML software systems
• Ability to ship customer-facing ML features, including prototyping, rigorous testing, monitoring, and reliable deployment
• Experience with major cloud platforms to deliver and operate high-scale ML workloads
• Deep understanding of modern ML techniques; experience in deep learning, reinforcement learning, or broader AI applications
• Bonus: hands-on work with agentic or novel AI systems
• Ability to produce production-quality code and services, while also rapidly building MVPs and iterating quickly to improve product outcomes
• Strong communicator comfortable partnering with cross-functional teams and contributing to the ML/AI community
• Creative problem-solver with the ability to tackle complex technical challenges
   

Technologies We Use and Teach
 

• Python (NumPy, Pandas, sklearn, XGBoost, etc)
• TensorFlow, Pytorch, keras, etc
• MySQL, Snowflake, GCP/AWS and Spark
   

We're working to build a more inclusive economy where our customers have equal access to opportunity, and we strive to live by these same values in building our workplace. Block is an equal opportunity employer evaluating all employees and job applicants without regard to identity or any legally protected class. We also consider qualified applicants with criminal histories for employment on our team, and always assess candidates on an individualized basis.