WaymoMountain View, California, USA$70-$70/hr
Bland AIPosted 5mo ago
Machine Learning Researcher, Multimodal LLMs
Machine Learning Researcher, Multimodal LLMs at Bland AI scores 93 out of 100 on AI centrality, which makes it a Level 4 role on this board.
AI in this role
Machine Learning Researcher, Multimodal LLMs
Location: San Francisco, CA or Remote
About Bland
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 $100M from leading investors including Emergence Capital, Scale Venture Partners, Y Combinator, and founders of Twilio, Affirm, and ElevenLabs.
The Role
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.
At Bland, we're not just thinking about text modeling. You will define how our agents listen, think, and act in real time, integrating streaming audio, tool execution, and dynamic context into a single coherent system. You will take ideas from research through production systems serving millions of calls per day.
What Makes You a Great Fit
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
Compensation & Benefits
Competitive salary: $160,000 – $280,000
Meaningful equity
Full healthcare, dental, vision
Office in Levi's Plaza, SF
High autonomy, high impact
Additional Information
Bland is an equal opportunity employer. We are committed to proving equal employment opportunities to all qualified applicants and employees and do not discriminate based on any legally protected characteristic.
Bland participates in the E-Verify employment verification program. All new hires are required to complete the Form I-9, and employment will be verified though E-Verify as part of the onboarding process.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- Walk me through how you've used Elevenlabs in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: Fine Tuning and Elevenlabs. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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