• We are building the newsroom of the future in Germany’s largest financial portal. • AI handles routine tasks so our editorial team can focus on what truly matters: context, analysis, and point of view. • AI-driven workflows for market reports, earnings recaps, economic updates, and much more • Development of multiple n8n flows as a central editorial asset • Wide selection of tools, API integration, quality assurance – end-to-end content repurposing at scale: articles, newsletters, and social media.

Role Description Block is building toward one of the most ambitious technical visions in our history: an AGI-enabled entity that fundamentally transforms how we deliver economic empowerment. We're assembling a world-class team of AI experts to design and ship autonomous agents and agentic workflows that operate across Square, Cash App, and the broader Block ecosystem. This work is about creating solutions—you'll be building AI that acts, decides, and completes real tasks for real users from across all of Block's business functions. As a Principal Engineer, you'll join as a senior individual contributor with significant technical leadership responsibilities. - Ship, architect, build, and own end-to-end delivery of autonomous agents and agentic workflows that deliver real business value for Block, ensuring reliability, safety, and performance at scale. - Design agent orchestration systems including planning, tool use, memory, evaluation, and multi-agent coordination at production scale. - Integrate and optimize frontier LLMs into agent architectures, making decisions on model selection, fine-tuning, prompt engineering, and context retrieval strategies. - Drive deeper model optimization work (fine-tuning, distillation, RLHF) where it unlocks agent capability or efficiency. - Lead detailed technical planning by breaking down ambitious objectives into concrete, sequenced tasks with clear ownership and execution paths. - Provide technical mentorship and guidance to engineers across experience levels, elevating team capabilities through code review, pairing, and knowledge sharing. - Partner closely with technical and non-technical stakeholders to translate business objectives into agent-powered product experiences. - Keep Block at the frontier by continuously evaluating emerging AI capabilities and making pragmatic tradeoffs across model performance, latency, cost, and user experience. - Foster a culture of technical excellence, high-quality delivery, rapid experimentation, and learning within your team and beyond. Qualifications - 15+ years of experience in software engineering or machine learning, with recent professional experience building autonomous agents or agentic workflows in production. - Deep experience building autonomous agents or agentic workflows in production environments—not just prototypes or demos. - Fluency in the core primitives of agentic systems: context management, planning, tool use, memory, evaluation, and multi-step reasoning. - Experience bringing frontier LLM capabilities into production products, with hands-on experience in prompt engineering, retrieval-augmented generation, and model optimization. - A track record of taking AI-powered products from zero to scale in fast-paced, product-driven environments, with the judgment that comes from operating in production. - Strong software engineering fundamentals with the ability to write production-quality code and make sound architectural decisions. - Experience providing technical leadership within teams—you've shaped technical direction, driven execution, and elevated others. - Product-minded engineering approach—you think in terms of user outcomes, not just model metrics. - Excellent collaboration and communication skills, with ability to build alignment across engineering, product, and design. - Comfort navigating extreme ambiguity in a domain that's evolving weekly. - Alignment with Block's mission of economic empowerment and using technology to create access and opportunity. Bonus Points For - Experience at leading AI organizations with a track record of translating research into production agent systems. - Background building or scaling agentic products at startups (including early-stage or pivoting companies). - Experience with model fine-tuning, distillation, or RLHF to improve agent performance. - Familiarity with agent evaluation, safety, and alignment challenges in production contexts. Benefits - Remote work - Medical insurance - Flexible time off - Retirement savings plans - Modern family planning

• Lead the planning, execution, and delivery of multiple AI initiatives, ensuring projects meet scope, timelines, quality expectations, and business objectives • Mentor and support AI Engineers by setting clear direction, providing coaching, and building a high-performing project team • Partner with stakeholders across product, science, clinical, operations, and engineering to define requirements, priorities, milestones, risks, and success metrics • Translate stakeholder needs into technical roadmaps, delivery plans, and resourcing strategies for AI-powered products and platforms • Guide solution design, software development, model integration, testing, deployment, and operational support across the AI project portfolio • Drive strong AI research and engineering practices across the team • Coordinate dependencies, remove blockers, and communicate project status, risks, and tradeoffs clearly to leadership and stakeholders • Balance innovation and experimentation with execution discipline, scalability, reliability, and compliance considerations • Contribute to hiring, onboarding, team planning, and continuous improvement of delivery processes and engineering standards

Role Description - Develop end-to-end machine learning solutions for challenging prediction and modeling problems. - Analyze datasets and define appropriate modeling approaches, validation strategies, and evaluation metrics. - Perform exploratory data analysis, feature engineering, and data preprocessing. - Train, tune, and evaluate machine learning models across tabular, text, image, and time-series datasets. - Review and validate the technical quality of machine learning projects and deliverables. - Identify opportunities to improve model performance through systematic experimentation and iteration. Qualifications - Must-Have: - Master's degree or PhD in Computer Science, Machine Learning, Statistics, Mathematics, Electrical Engineering, or a related field from a top-tier university. - 2+ years of professional experience in machine learning, applied AI, data science, or a closely related field. - Strong proficiency in Python and modern machine learning frameworks (e.g., scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow). - Demonstrated experience building end-to-end machine learning solutions, including data preparation, model development, validation, and evaluation. - Strong understanding of model evaluation metrics, validation methodologies, and experimental design. - Experience with one or more of the following areas: tabular machine learning, natural language processing, computer vision, recommendation systems, ranking systems, time-series forecasting. - Ability to work independently on open-ended machine learning problems and deliver high-quality technical outputs. - Preferred: - PhD from a leading research university. - Experience at leading technology companies, AI labs, research institutions, or high-growth startups. - Participation in competitive machine learning or data science competitions. - Experience optimizing models against performance-based evaluation metrics. - Familiarity with advanced techniques such as ensembling, hyperparameter optimization, transfer learning, foundation model fine-tuning, or reinforcement learning. - Publications, patents, or significant open-source contributions in machine learning or AI. - Experience reviewing, mentoring, or evaluating the work of other machine learning practitioners. Application Process - Upload resume - AI interview based on your resume - Submit form Resources & Support - For details about the interview process and platform information, please check: Interview Process - For any help or support, reach out to: support@mercor.com - PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.