Top AI & Machine Learning Jobs

Lead strategy and execution for AI-powered risk automation products. Identify automation opportunities, define product requirements, partner with ML/data/engineering/design, run experiments, set metrics for accuracy, safety, and reliability, and drive cross-functional launches to improve decision quality and operational efficiency.

Senior individual contributor building and maintaining underwriting and credit decisioning ML systems for Cash App Borrow and Afterpay. Responsibilities include feature engineering, model training, calibration, experimentation, deployment, monitoring, and portfolio-level analysis. Collaborate with cross-functional teams to align models with business and regulatory goals and develop AI-native engineering workflows and governance for reliable, auditable model development.

Graduate research interns will own end-to-end projects developing customer world models and proactive intelligence. Work spans representation learning, foundation models, reinforcement learning, agentic decision systems, and evaluation. Tasks include designing methods, running experiments, publishing findings, and potentially shipping models into production to impact customer-facing products.

Graduate research internship to own end-to-end research on Customer World Models and proactive intelligence: design representations, develop methods (foundation models, RL, causal reasoning, agentic systems), run experiments, publish, and help ship ML systems that anticipate and act on customer needs.

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 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.

Lead AI risk assessments for Generative AI and LLM use cases, ensuring compliance and safe deployment while collaborating with stakeholders across various departments.