Top AI & Machine Learning Jobs

Embed with customers to design, build, and deploy production agentic AI systems. Architect multi-agent workflows, prototype and harden LLM-based agent frameworks, implement stateful memory and evaluation/safety guardrails, optimize latency and cost, and translate field feedback into platform improvements while collaborating with product and engineering teams.

Lead design, deployment, and optimization of production-scale LLM inference systems. Embed with customers to debug latency, profile GPU usage, implement cluster-scale strategies (prefill/decode disaggregation, KV-cache routing, tiered caching, MoE parallelism), drive hardware efficiency (quantization, parallelism, batching), build internal tooling, and contribute improvements upstream to open-source inference frameworks.

Technical leader designing and implementing massive-scale, stateful multi-agent multi-turn simulation and evaluation systems. Build persona synthesis pipelines, what-if benchmarking frameworks, durable workflow orchestration, and high-performance APIs while integrating LLMs and agentic architectures. Drive architecture, mentor engineers, lead cross-functional strategy, and ensure scalability, reliability, and observability for AI feedback and evaluation infrastructure.

Lead and grow the Inference Orchestration engineering team to design, build, and operate Kubernetes-based AI infrastructure at scale. Drive scheduling, GPU utilization, topology-aware placement, checkpoint/restore for long jobs, fault tolerance, model distribution, security isolation, and cross-functional delivery to meet performance, cost, and reliability goals.