Top Tech Jobs & Startup Jobs

Lead design and optimization of data models and pipelines for compliance and risk; standardize metrics and documentation; build data quality, lineage, and monitoring (including AI agents for automation); manage ETL scheduling, on-call pipeline support, and collaborate with product and non-technical partners to translate business needs into automated, production-ready data solutions.

Design, build, and operate production ML decision systems to detect and prevent payment fraud, account takeover, identity abuse, merchant/marketplace risk, scams, and other adversarial activity. Own end-to-end production lifecycle: data contracts, low-latency inference, batch scoring, feature quality, deployment, monitoring, incident response, rollback, and feedback loops. Develop AI-assisted workflows and reusable decision capabilities while partnering with modelers, product, compliance, and operations.

Design, build, and deploy transformer-based ML and LLM systems to automate risk investigations and decisioning. Own end-to-end pipelines (data ingestion, prompt tuning, orchestration, productionization, monitoring) and collaborate with product, engineering, and operations to deliver copilot/autopilot workflows that improve analyst productivity and eliminate manual reviews.

Design, build, and operate production ML signal systems—ranking, retrieval, recommendations, propensity, and next-best-action—covering feature/candidate generation, serving, experimentation, monitoring, and feedback. Define signal contracts (freshness, provenance, confidence), evaluate long-term impact (trust, fairness, compliance), and partner across product, data, and risk teams to deliver reusable customer-intelligence capabilities.

Lead the delivery of ML initiatives, define roadmaps with cross-functional teams, and develop ML models for conversational agents and smart tools, enhancing customer support.

As a Product Manager for GTM Automation, you will lead strategies for AI-powered products, identify automation opportunities, and collaborate across teams to optimize workflows and improve efficiency.

As a Senior Machine Learning Engineer in Model Risk Management, you will evaluate and validate models that assess risk in lending and fraud, ensuring their robustness and reliability. You will collaborate with model owners, tackle model challenges, and build evaluation tools critical for understanding model performance.

Own end-to-end subsidiary governance reporting across 11 regulated entities: design cadence, coordinate with MLROs and compliance leads, synthesize cross-entity intelligence, produce Board-quality governance materials, maintain reporting templates, and identify capability gaps for prioritization.

The Staff Software Engineer will lead technical strategies for the Cash App Banking team, overseeing architectural decisions, mentoring engineers, and developing financial products that improve customer banking experiences.

As a Staff Software Engineer, you will lead technical strategies, drive architectural decisions, mentor engineers, and develop consumer banking solutions using various technologies.