Researcher, Post Training

Cartesia
California, San Francisco
Workplace: OnsiteFull timeUSD 180,000 - 350,000 annuallyFunction: Research & Scientific (R&D)Skills: ["Collaboration","Communication","Problem-solving"]

Researchers on Cartesia's Post-Training team design and evaluate alignment methods for multimodal models, building experimental systems and production-ready tools to improve model reasoning, grounding, and human alignment. You will own research initiatives, develop post-training evaluation frameworks, and collaborate with research, product, and platform teams to scale reliable AI systems.

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Cartesia
Cartesia
10 months ago

Researcher, Post Training

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Last checked: 6 hours agoStatus: Live

Job Summary

Researchers on Cartesia's Post-Training team design and evaluate alignment methods for multimodal models, building experimental systems and production-ready tools to improve model reasoning, grounding, and human alignment. You will own research initiatives, develop post-training evaluation frameworks, and collaborate with research, product, and platform teams to scale reliable AI systems.
Location: California, San Francisco
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Own research initiatives to improve the alignment and capabilities of multimodal models
  • •Develop new post-training methods and evaluation frameworks to measure model improvement
  • •Partner closely with research, product, and platform teams to define best practices for creating specialized models
  • •Implement, debug, and scale experimental systems to ensure reliability and reproducibility across training runs
  • •Translate research findings into production-ready systems that enhance model reasoning, consistency, and human alignment

Pay and Benefits

Salary: USD 180,000 - 350,000 annually

Key Requirements

  • •Deep knowledge of preference optimization and alignment methods, including RLHF and related approaches
  • •Experience designing evaluations and metrics for generative or multimodal models
  • •Strong engineering and debugging skills, with experience building or scaling complex ML systems
  • •Ability to trace and diagnose complex behaviors in model performance across the training and evaluation pipeline
  • •Experience with multimodal model training (e.g., text, audio, or vision-language models)
Experience:MultimodalAIMachine learningResearch
Skills:CollaborationCommunicationProblem-solving
Languages:English

Company Brief

Cartesia
Builds real-time multimodal and voice AI (Sonic) that generates expressive, low-latency speech for conversational agents and on-device experiences, serving developers and enterprises with APIs and SDKs.
Industry: AI & Machine Learning
Company Size: Small (11 to 50 employees)
Growth: Growth Stage Startup
Funding: Series A
Headquarters: San Francisco, United States
Founded: 2023
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