Machine Learning Researcher, Multimodal LLMs

We are looking for someone to contribute to the development of our next-generation multimodal LLM stack, combining speech, text, tools, and real-time reasoning into a single unified system. You’ll be responsible for building industry-leading conversational AI models that power Bland’s agent, and taking them all the way from idea to production.

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

• You can go from idea * dataset * experiment * conclusion in days
• You know how to design experiments that actually answer the question

Product Intuition

• Strong sense for what makes an interaction feel natural vs robotic
• Ability to translate abstract modeling ideas into user-facing improvements

Builder Mentality

• You take ownership from research through deployment
• You thrive in ambiguous, fast-moving environments
• You care about impact, not just elegance

How You Show Up

• You think in systems, not just models
• You obsess over latency, correctness, and real-world behavior
• You are comfortable discarding ideas quickly when data disagrees
• You push toward simple abstractions for complex problems

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

• Competitive salary: $180,000 - $260,000
• Meaningful equity
• Full healthcare, dental, vision
• Office in Jackson Square, SF
• High autonomy, high impact

At Bland.com, our mission is to empower enterprises to build AI phone agents at scale. Voice is quickly becoming the primary interface between businesses and their customers, and we are building the models and infrastructure that make those interactions feel natural, reliable, and genuinely human.

We’ve raised $65M from leading investors including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs.