Top AI & Machine Learning Jobs

Lead hands-on design and delivery of production-ready agentic AI applications and platform capabilities. Drive architecture, SDLC best practices, observability, security, and automation. Collaborate with Applied AI, Product, and Platform teams to move projects from prototype to governed production while mentoring engineers and improving developer productivity using AI-enabled tooling.

Design and build scalable, production-grade AI-enabled and agentic applications and platforms. Implement architectures, CI/CD, testing, observability, and secure, reliable distributed systems while improving engineering productivity via AI-assisted workflows.

Lead client engagements to define, architect, build, and deploy Generative AI and agentic AI solutions. Translate business problems into LLM/agent-based designs, drive hands-on delivery (prompts, RAG, agents, evaluation), manage multidisciplinary teams, ensure security/governance/responsible AI, and support presales and scaling of AI capabilities.

The Principal AI Engineer leads the design and operationalization of complex AI systems, architecting multi-agent solutions while ensuring safety, reliability, and performance. They mentor engineers and improve processes and products based on measurable outcomes.

Lead engineering for agentic AI products and platforms: define architecture and strategy, build and scale teams and reusable frameworks, drive production-grade agent systems (orchestration, memory, tool integration, observability, safety), partner with Product/Data/Security, and enable enterprise adoption through tooling, standards, and measurable success metrics.

Lead hands-on development, deployment, and operation of production AI and agentic systems. Build ML services, pipelines, APIs, and model-serving/monitoring/retraining capabilities. Partner with data scientists and platform/security teams to productionize models at scale, ensure reliability, observability, security, and governance, and mentor engineers.

Lead design, build, and production deployment of AI and agentic systems. Develop and operate ML services, pipelines, and APIs; productionize models, implement model serving, monitoring, evaluation, and retraining; collaborate with data scientists and platform, security, and infrastructure teams to ship reliable, secure, and governed AI at scale.

Lead design, development, and production deployment of AI and agentic systems. Build and operate ML services, pipelines, model serving, monitoring, evaluation, and retraining. Collaborate with data scientists and platform/security teams to productionise models, ensure reliability, observability, security, and governance, and mentor engineering peers.

Lead hands-on development and production deployment of AI and agentic systems. Build and operate ML services, pipelines, model serving, monitoring, and retraining. Partner with data scientists to productionize models at scale, ensure reliability, security, and governance, and collaborate with platform, security, and infrastructure teams. Provide technical leadership and mentorship.

Lead development and production deployment of AI and agentic systems. Build and operate ML services, pipelines, model serving, monitoring, evaluation, and retraining. Partner with data scientists to productionize models, ensure reliability, security, and governance, and collaborate with platform, security, and infrastructure teams. Provide technical influence and mentorship.