Top Senior Machine Learning Jobs in Las Vegas, NV

Lead MLOps for production ML lifecycle: deploy and serve models, build scalable reproducible pipelines for large protein-design workloads, implement CI/CD and observability, optimize GPU/accelerated compute, and enable self-service tooling for researchers.

Lead technical pre-sales and enterprise rollouts by owning infrastructure strategy, PoCs, migrations (on‑prem to cloud), DMS/CRM integrations, InfoSec discussions, and stakeholder engagement with C-level sponsors to enable scalable deployments and upsell opportunities.

Build and productionize large-scale ML models and pipelines for query understanding and personalization. Work on autocomplete, query tagging/NER, query expansion, intent modeling, and LLM-powered natural-language search. Collaborate cross-functionally to design, deploy, and monitor batch and real-time systems, leveraging modern ML infrastructure and tooling to improve search relevance across Airbnb products.

The Senior Machine Learning Engineer will design, train, and deploy ML models for optimizing revenue in advertising, taking ownership of product development and leading the ML discipline.

The Lead Machine Learning Engineer will design and evaluate models for autonomous driving systems, mentor junior engineers, and utilize large datasets to improve ML capabilities at May Mobility.

Lead the development of device intelligence and fingerprinting systems by designing backend services, collaborating on integrations, and applying advanced machine learning algorithms to enhance security and combat fraud.

The role involves applying AI/ML techniques to develop model systems for healthcare, collaborating across teams, and conducting R&D.

Design, fine-tune, evaluate, and deploy LLM-driven, user-facing browser features using RAG, embeddings, prompt engineering, and modern ML tooling. Lead end-to-end model lifecycle, run production experiments, collaborate with product and engineering, and document and review work with an emphasis on privacy, latency, and usability.

Lead program delivery for engineering teams at Arine, optimizing internal processes and ensuring timely execution of technical programs while facilitating Agile methodologies.

Own and improve recommendation and search systems across feed, discovery, and search. Build retrieval and ranking (candidate generation, embeddings, two-tower models), run experiments, create user/content/session representations, and ship production ML systems with monitoring to improve retention, engagement, and content distribution.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.