Direct from source · No middlemen
14 open positions · Updated 3 weeks ago
14 Pandas roles across 7 companies, most in AI/ML; typical advertised salary $256.4k
Who is hiring (7 companies)
Role types
Work arrangement: 10 hybrid · 1 on-site · 3 not stated
Advertised salaries: p25 $233.5k · median $256.4k · p75 $320k (from 10 disclosed annual salaries, USD)
Counts are open roles Joblaze currently tracks on company career pages for this exact skill/location; salaries are advertised minimums, annual, converted to USD.
Showing 14 of 14 positions
Search with filters →Join Snorkel AI as a Staff Applied AI Engineer to deliver impactful AI solutions and drive customer success.
Join Mirage as a Product Data Scientist to drive data-driven decisions for our innovative AI video tools.
Join Attentive as a Staff Software Engineer to build and scale ML systems for personalized marketing experiences.
Join Valence as a Staff Software Engineer to shape AI-powered leadership coaching for Fortune 500 companies.
Join Braze as a Data Scientist II to collaborate with clients and enhance AI deployment strategies in a passionate team.
Join Attentive as a Senior Machine Learning Engineer to build and scale ML systems for real-time personalization in a fast-paced environment.
Join Attentive as a Senior Software Engineer to shape the future of our high-throughput event streaming platform.
Join Attentive as a Staff Software Engineer to build and scale ML systems for personalized marketing experiences.
Join Attentive as a Senior Machine Learning Engineer to build and scale ML systems for real-time personalization in a dynamic startup environment.
Lead and build the Forward Deployed Engineering team to deliver high-quality datasets for critical AI initiatives.
Join Snorkel AI as a Research Scientist to bridge cutting-edge research and real-world AI systems in a dynamic environment.
Own the medium-range demand forecast for infrastructure resources at Anthropic, supporting sourcing and workload optimization.
Join Anthropic as a Performance Engineer to optimize AI inference systems for throughput, latency, reliability, and correctness.