Top AI & Machine Learning Jobs

Lead design and deliver multi-cloud AI/ML solutions that ingest and correlate telemetry (metrics, logs, traces), build predictive anomaly detection and forecasting models, automate closed-loop remediation, integrate with ticketing systems, and provide self-service or conversational interfaces to reduce MTTR and ticket volume.

Leads enterprise AI transformation strategy and execution, including roadmap development, scalable AI/ML infrastructure, application deployment, data pipelines, APIs, governance, security, privacy, and ethical AI practices. Partners with executives, data scientists, product managers, and engineers, evaluates emerging AI technologies, tracks initiative ROI, drives organizational change, and mentors teams to increase AI adoption and literacy.

Develop and deploy statistical, machine learning, mathematical, and optimization models for Prime Finance. Responsibilities include forecasting borrow rates and demand, optimizing pricing and inventory allocation, researching alpha signals and hedging strategies, building analytics infrastructure, managing model risk, and communicating results to trading, technology, risk, and senior stakeholders. The role also mentors junior researchers and documents methodologies.

Lead and mentor an agile engineering team to design, build, test, and operate secure, cloud-native production software. Provide technical direction, deliver high-quality code, drive product design decisions, and advocate firmwide engineering practices while applying AI/ML expertise.

Leads development and operation of secure, scalable AI/ML cloud platforms. Designs AWS infrastructure, Kubernetes environments, GPU workloads, infrastructure-as-code, deployment tooling, APIs, and MLOps workflows. Drives reliability, observability, automation, model serving, and enterprise LLM operationalization while partnering with data science and engineering teams. Coaches teams on responsible, secure use of AI-assisted development tools and establishes validation standards for production software.

Leads architecture, development, deployment, and optimization of enterprise LLM and GNN serving platforms across AWS, cloud, and on-premises environments. Establishes MLOps and LLMOps strategies, agentic AI engineering standards, automation, governance, observability, and operational practices. Optimizes inference for throughput and latency using Triton and vLLM, partners with data science and SRE teams, and influences senior stakeholders on secure, responsible AI adoption.

Develops data science and analytics solutions for Global Payments by exploring transaction flows, identifying high-impact use cases, delivering actionable insights, and supporting data-driven product strategy. Collaborates with stakeholders and product managers, translates complex data requirements into analytical solutions, promotes data products, and contributes to robust data assets and product enhancements.

Lead the design and development of production-grade agentic AI applications for Markets Operations. Build reusable AI architecture patterns, orchestration frameworks, context management, evaluation pipelines, guardrails, APIs, infrastructure, and monitoring. Partner with researchers, engineers, data scientists, and operations stakeholders to deliver secure, reliable, compliant AI solutions. Drive continuous improvement, document technical decisions, influence architecture, and mentor engineers.

Conduct ML/DL research to develop predictive models from large market datasets, integrate models into systematic trading strategies, contribute to AI/ML libraries, and deploy production algo systems with P&L responsibility across FX, Rates, Commodities, and Credit.

Designs, develops, debugs, and maintains secure production software components; applies SDLC and agile practices; leverages enterprise AI-assisted coding tools responsibly; analyzes large datasets to inform secure, resilient application development; contributes to automation, code review, and team culture.