Ready to create foundation models for Embodied AI?

Join a pioneering startup developing the foundation layer for the next big AI unlock, naturalness of conversation, from the speech visual element, the interruptions, turn taking. This in turn will change the game for embodied agents with natural behaviours, real-time expression, and conversational intelligence that goes far beyond current avatar technology.

This Research Scientist role focuses on advancing embodied AI through groundbreaking research on Audio to Video models. While existing solutions rely on looped animations with basic lip-sync, this company is building behaviour driven models that drive authentic, real-time interactions capable of natural conversation flow, interruption handling, and emotional expression.

Founded 18 months ago by an exceptional team where 7 out of 12 members hold AI PhDs, they're solving fundamental challenges in Embodied Intelligence. Their beta platform already demonstrates sophisticated real-time avatar systems with proprietary voice models and behaviour engines working in harmony.

The company is building foundational technology that learn from two-way video interactions, creating systems that understand and respond to both verbal and non-verbal cues. Their research sits at the intersection of computer vision, conversational AI, and real-time generation.

Your focus:

• Conduct cutting-edge research in avatar modelling, behaviour generation, and style transfer
• Develop sophisticated facial and body dynamics systems for expressive avatars
• Create conversational AI systems that drive natural avatar behaviour through LLMs
• Build real-time multimodal generation pipelines integrating visual, audio, and text
• Contribute to Behaviour model development for authentic interaction patterns
• Collaborate with engineering to productionise research into real-time systems
• Publish findings at top-tier conferences while deploying in real-world applications

Technical challenges: You'll work with cutting-edge techniques including diffusion models, flow matching, and Gaussian splatting. The focus is on dyadic conversational avatar development and natural behaviour modelling, emphasising authentic real-time interaction over static visual perfection.

Requirements:

• PhD in Computer Vision, Machine Learning, or related field
• Strong publication record at top conferences (CVPR, NeurIPS, ICCV, ECCV, ICML, ICLR, SIGGRAPH, etc). Recent avatar research publications within the past 2 years (essential)
• Expertise in flow matching and diffusion models
• Experience with one or more: conversational avatars or behaviour modelling or real-time multimodal generation
• PyTorch proficiency and large-scale training experience

Nice to have:

• Industry experience deploying ML models in real-time applications
• Voice research publications
• Background in interactive systems or conversational AI

Environment: You'll join a distributed team working primarily in Pacific Time zones, collaborating with specialists in avatar development, voice research, and behaviour modelling. The culture emphasises high ownership, velocity with purpose, and collaborative problem-solving in a fast-moving research environment.

Package:

• Competitive salary, $200k- $300k base (based on experience)
• Meaningful equity package
• Comprehensive healthcare (90% covered)
• Unlimited PTO
• Fully remote work with regular team offsites
• Life insurance and disability coverage

Location: Fully remote position, globally, with preference for Pacific Time alignment.

If you're excited about conducting pioneering research in the next challenge of embodied intelligence while shaping the future of human-AI interaction, this offers an exceptional opportunity to work on genuinely transformative technology.

Ready to help create AI that feels present, not just functional?

Contact Marc Powell at Techire AI. All applicants will receive a response.

Ready to build AI agents that actually solve real-world problems?

Join a well-funded AI startup developing the next generation of agentic AI systems - general-purpose models capable of solving real-world user problems end-to-end with minimal prompting.

They're building an agentic AI desktop assistant that integrates deeply with operating systems, positioning as a potential competitor to OpenAI's operator. With over $40 million in funding, they're pushing the boundaries of what's possible in LLMs, reinforcement learning, and autonomous AI systems.

This role offers the rare opportunity to work on foundational AI research that directly translates into practical applications. You'll be building technology that transforms how people interact with computers, creating AI agents that don't just talk, but actually perform complex tasks autonomously.

Your focus:

You'll join the foundational AI research team tackling some of the most challenging problems in AI today. Your work will span from theoretical research to practical implementation, with the goal of building core models that surpass existing capabilities while maintaining highest accuracy and longest possible context windows.

As a Research Engineer, you'll design and implement cutting-edge LLM architectures specifically for agentic behaviour and real-world task solving. You'll own components of the RL training pipeline, including reward model development, evaluation, and deployment. Working with high-quality datasets for supervised fine-tuning and RL will be central to your role, as will experimenting with novel training algorithms for agentic systems.

You'll contribute to benchmark design and evaluation strategies for both reward models and policy models, staying at the frontier of LLM, RL, and agent research whilst turning theory into scalable systems that can be deployed at scale.

You should have:

A deep understanding of LLM post-training, fine-tuning, and evaluation, especially in the context of agents. Experience designing or training reward models for alignment or task optimisation is essential, along with hands-on experience implementing RLHF, DPO, or similar methods to align language models with human feedback.

You'll need strong intuition for dataset quality - knowing how to spot problematic data and craft effective supervision. Fluency with PyTorch, Hugging Face, and modern LLM libraries is crucial, as is the ability to prototype and scale new ideas quickly.

The ideal candidate can implement novel training algorithms, architectures, or evaluation strategies from research papers or original ideas, bringing both theoretical understanding and practical engineering skills to complex AI challenges.

Nice to have:

Experience scaling LLMs beyond 10B parameters would be valuable, as would prior research experience in LLMs, RL, or reward learning. Publications in relevant venues are appreciated but practical implementation experience is equally valued.

What they offer:

This is an opportunity to work with a top-tier team of researchers and engineers building aligned, general AI systems that are truly helpful and deployable. Your work will directly shape how AI interacts with the real world, moving beyond conversational interfaces to systems that perform meaningful tasks.

The compensation reflects the senior nature of the role: $200k-$250k base salary (negotiable based on experience) plus significant equity in a well-funded company positioned at the forefront of agentic AI. They provide comprehensive benefits and visa sponsorship for exceptional candidates.

Office based near Palo Alto, they're looking for energetic, fast-paced individuals who bring fresh excitement to the space and want to push the boundaries of what's possible with autonomous AI systems.

If you're excited about building AI agents that move beyond conversation to actual task completion, this could be your opportunity to make a lasting impact on the future of human-computer interaction.

Ready to help define the next generation of AI? All applicants will receive a response.