Bland AIMachine Learning Researcher, Multimodal LLMs
Bland AI is hiring a Machine Learning Researcher, Multimodal LLMs for a remote role open to applicants in United States. It pays $160k-$280k a year and Level rates it ; you can apply on Bland AI.
Level's read on this job
- Builds AI ●●●● is how Level rates this role: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include Elevenlabs, fine tuning and machine learning.
- Level classifies it as a senior role.
- Level lists 16 other open roles at Bland AI.
AI in this role
Research and develop next-generation multimodal LLM stacks and real-time conversational AI models.
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.
How we rate this
Machine Learning Researcher, Multimodal LLMs at Bland AI rates 100 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
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?
- Tell me about a project where machine learning was part of your work. What did you do?
- Tell me about a project where multimodal llms was part of your work. What did you do?
- Tell me about a project where conversational ai was part of your work. What did you do?
- Tell me about a project where speech recognition was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Machine learning, Multimodal LLMs, Conversational AI, and Speech Recognition. 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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