Top AI & Machine Learning Jobs

Lead and build a US-based data science capability while remaining hands-on: write code, design, deploy, and maintain production ML models on GCP (Vertex AI), mentor junior data scientists and ML engineers, establish workflows/standards and CI/CD, collaborate with US and UK data teams and product stakeholders, and implement real-time/event-driven solutions (Kafka).

Partner with AI Engineering leadership to drive strategy, portfolio delivery, governance, and financials for AI/GenAI initiatives. Lead cross-functional programs from ideation to production, manage budgets and vendors, establish AI lifecycle governance and risk controls, and deliver executive reporting to ensure adoption, stability, and business outcomes.

Own, build, and optimize Spark-based production data pipelines and ML data lake to support recommender systems and personalization. Scale cluster configurations on GCP Dataproc, ensure data quality and accessibility, support ML engineers for model development, resolve performance bottlenecks, and collaborate on platform architecture to deliver reliable data products that drive business value.

The Applied AI Engineer will build and maintain AI agents, manage integrations and monitor performance, ensuring quality and continuous improvement of AI tools at Zello.

Lead cross-functional programs for AI networking infrastructure, ensuring alignment between network architecture, hardware development, and operational readiness. Manage supplier relationships and oversee the technical roadmap for scalable AI infrastructure delivery.

Own and administer Salesforce and NetSuite while designing and deploying production-grade AI-driven automations and agent workflows. Ensure data governance, PHI/HIPAA compliance, release management, and quote-to-cash integrity. Partner cross-functionally to prioritize work, coach teams, document systems, and measure impact of automation on operations and revenue.

Design, build, and maintain scalable self-service data and ML platform tools and workflows. Mentor junior engineers, collaborate with cross-functional teams, implement monitoring/alerts, drive infrastructure improvements, integrate new technologies, and produce technical documentation to support reliable, scalable data products and pipelines.

Build the core AI platform and high-performance Rust backend powering an AI-native trading copilot. Implement streaming responses, low-latency tool execution, caching, orchestration of models and tools, secure APIs, auditing/tracing, and safe, auditable trading action infrastructure. Partner with product and frontend to enable AI-native UX and translate trading domain requirements into resilient platform primitives.

Lead and build an Enterprise AI organization to define strategy, platforms, governance, and standards. Deliver scalable AI platforms (LLM gateways, model registries, vector DBs), enable business adoption, embed responsible AI and compliance, partner across Security, Legal, Finance, and drive measurable AI use cases and ROI while managing a small, cross-functional AI architecture and engineering team.

Build and ship computer-vision models end-to-end: dataset curation, training, deployment, and monitoring across cloud and roadside edge hardware. Optimize for high-volume inference, accuracy, efficiency, and real-world robustness while collaborating cross-functionally and iterating rapidly.