Machine Learning Researcher, Multimodal LLMs

Responsibilities

• Contribute to the development of next-generation multimodal LLM stack, combining speech, text, tools, and real-time reasoning into a single unified system.
• Build industry-leading conversational AI models that power Bland's agent, taking them from idea to production.
• Define how agents listen, think, and act in real time, integrating streaming audio, tool execution, and dynamic context.

Requirements

• Strong LLM / Multimodal Background: Experience with LLMs, multimodal models, or speech-language systems. Deep understanding of prompting, fine-tuning, and alignment techniques. Familiarity with neural audio codecs and modern multimodal LLM techniques.
• Fast Experimental Loop: Ability to go from idea → dataset → experiment → conclusion in days. Design experiments that answer questions.
• Product Intuition: Strong sense for natural vs robotic interactions. Translate abstract modeling ideas into user-facing improvements.
• Builder Mentality: Take ownership from research through deployment. Thrive in ambiguous, fast-moving environments. Care about impact over elegance.
• Think in systems, obsess over latency, correctness, and real-world behavior. Comfortable discarding ideas quickly. Push toward simple abstractions.

Nice-to-Haves (Bonus Points)

• Experience with real-time voice systems or conversational AI.
• Background in tool-using agents or agent frameworks.
• Experience with multimodal datasets (audio + text + actions).
• Contributions to LLM or speech-related research or open source.

Compensation & Benefits

• Competitive salary: $180,000 – $260,000
• Meaningful equity
• Full healthcare, dental, vision