Ml Serving Jobs

AirOps seeks a hands-on Lead Data Scientist to architect and deliver production NLP, search, and LLM systems that improve content discovery and business outcomes for leading brands.

Help architect and scale a production ML inference platform at Tamarind Bio to serve hundreds of biological models and support rapid customer growth.

Specter is hiring an ML Infrastructure Engineer to design and scale training pipelines, optimized model serving, and continuous production workflows for real-time edge perception systems.

August is hiring a Founding AI Engineer to design and deploy production agent systems that automate legal workflows for mid-market law firms.

Palo Alto Networks is hiring a Principal MLOps Engineer to lead ML platform architecture and production deployments for DLP detection systems from its Santa Clara campus.

Lead the architecture and delivery of production-grade AI systems for cyber operations, building resilient agent orchestration, MCP serving infrastructure, and advanced prompt engineering patterns.

Bjak seeks an MLOps Engineer to run and scale open-source LLMs into production, optimizing for cost, latency, and reliability while working in a flexible hybrid model.

Lead the design and delivery of production-scale LLM, knowledge-graph, and ML systems for Workday’s Evisort AI team to transform contract intelligence and enterprise document workflows.

Aura is hiring a Senior Software Engineer (AI Backend) to design and operate scalable Python backend systems, deploy ML/LLM-driven features, and manage cloud infrastructure in a remote role.

Quilter is hiring a Senior ML Ops Engineer to own and scale production ML training and inference infrastructure for automated PCB layout generation.

Join a fast-growing, venture-backed GovCon SaaS startup as a Senior ML/AI Engineer to own production classification and recommendation systems and integrate LLM-driven capabilities into core product workflows.

Senior engineering role to design and lead scalable, secure AI and data platforms that enable analytics, ML/LLM workflows, and data-driven decisions across a distributed, remote-first US team.