Top AI & Machine Learning Jobs

Build complete applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, deploy solutions, instrument usage and outcomes, evaluate AI-generated output for security and quality, engage with customers, and document effective prompts and development patterns.

Build complete applications, workflow automations, and basic AI agents by directing AI coding agents. Translate customer needs into specifications, deploy full-stack solutions, instrument usage and outcomes, evaluate AI-generated work for security and reliability, engage with customers, and document effective prompts and development patterns.

Build and deploy full-stack applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, evaluate AI-generated solutions for security and reliability, instrument products, analyze usage and outcome metrics, identify automation opportunities through customer conversations, and document effective prompts and development patterns.

Build and deploy complete applications, workflow automations, and basic AI agents using AI coding agents. Translate customer needs into specifications, instrument solutions, evaluate AI-generated output for security, privacy, reliability, and quality, and iterate based on usage and outcome metrics. Participate in customer conversations to identify automation opportunities and document effective prompts and development patterns.

The Senior AI Software Engineer will design and build secure systems for high value senders, focusing on trust and reliability in financial transactions. Responsibilities include technical design, system architecture, team mentoring, and using AI tools to enhance software delivery.

Lead design, implementation, and scaling of end-to-end ML systems including feature pipelines, model training, evaluation, deployment, and monitoring. Partner with cross-functional teams to productionize models, apply MLOps best practices (automated retraining, CI/CD, drift detection), and mentor engineers to maintain high code and system quality.

Design, build, and productionize real-time fraud detection models. Advance adversarial-domain techniques (graph, sequence, anomaly detection), design robust evaluation for biased/delayed labels, ensure low-latency reliable deployment, monitor models in production, and collaborate with data scientists and stakeholders to translate fraud signals into modeling solutions.

Build and ship agentic LLM systems for Treasury: cash monitoring, funding execution, narrative generation, and discovery-to-deployment pipelines. Create reusable agent infrastructure, governance, evaluation, and partner with engineering to ensure data accuracy while embedding with operators to scope and iterate solutions.

Lead end-to-end product builds by orchestrating AI coding agents to create applications, automations, and basic agents. Translate customer problems into deployable solutions, instrument usage and outcomes, evaluate AI output for security/privacy/quality, engage with customers to find automation opportunities, and document prompts, patterns, and approaches for the team.

Lead end-to-end ML lifecycle: data exploration, model training, evaluation, deployment, and monitoring. Design and scale batch and real-time feature pipelines, partner cross-functionally to productionize models, implement MLOps (CI/CD, retraining, drift detection, observability), and mentor engineers to maintain high code and system quality.