Ready to tackle the number one problem facing widespread AI adoption?

Join a pioneering company developing the world's first Agent to supervise Agents, LLMs and AI systems. As we move toward an increasingly autonomous AI future, scalable oversight isn't just important—it's essential for safe AGI deployment.

You'll work on the world's first Agent which supervises Agents, LLMs and AI systems. Gone are the days of basic evaluations—this completely automates the evaluation process and automatically debugs AI agents, giving intelligent feedback on how to fix any failures, planning issues or systemic issues. While AI engineers currently spend hours combing through agent traces searching for planning mistakes and tool use errors, this technology makes the process instantaneous and comprehensive.

This role offers an opportunity to solve fundamental research problems at the intersection of LLM post-training, reinforcement learning, and agents. You'll work on post-training, creating realistic RL environments for agent evaluation, building the next generation of agentic evaluation systems and developing proprietary benchmarks for emerging AI capabilities.

Your research focus:

• Core Research impacting their main Agent platform
• Develop cutting-edge benchmarks that evaluate LLM and agent capabilities as they emerge
• Create challenging RL environments that organically evaluate agents under realistic conditions
  Advance agentic evaluation methodologies beyond traditional LLM-as-a-Judge approaches
• Build and improve evaluator models that provide systematic oversight of autonomous systems
• Publish research findings in collaboration with top AI research labs

The role balances research with implementation, allowing you to see your theoretical contributions deployed in production systems used by industry leaders. You'll work directly with the founding team to shape the technical direction of AI supervision technology. They also co-publish papers with top research labs.

You should have:

• Strong hands-on research experience in LLM post-training or RL, or agent research
• Publication record at top conferences (NeurIPS, ICML, EMNLP, ACL, ICLR)
• Experience with LLM fine-tuning and understanding of transformer architectures
• Track record of following recent research and implementing state-of-the-art methods
• PhD in Computer Science or related field (preferred but not required)
• Ability to move quickly and thrive in a startup environment

You'll join a small but exceptionally high-calibre team working on problems that will define the future of responsible AI systems and AI safety. The company has proven market demand with existing enterprise customers (OpenAI, NVIDIA, Meta and more) and strong backing, allowing you to focus on breakthrough research with real-world impact.

Your package includes:

• Salary up to $300,000 (negotiable based on experience)
• Significant stock in a fast-growing company
• Comprehensive benefits, 401k, and unlimited PTO
• Relocation assistance available and sponsorship

You'll work from San Francisco, NYC also considered.

Ready to help ensure AI systems are safe and reliable as we approach AGI?

If you're excited about solving the most critical challenge in AI safety while publishing cutting-edge research, we'd love to hear from you. All applicants will receive a response.

Build production systems that bring 3D AI models to life in real-world applications

Ready to bridge cutting-edge 3D computer vision research with robust, scalable production systems? This ML Engineer role focuses on deploying 3D perception models into live agentic workflows where reliability and performance are paramount.

You'll be joining a well-funded startup developing AI agents for advanced design and manufacturing. Your role centres on creating the infrastructure that makes 3D understanding truly practical - from real-time inference pipelines to comprehensive monitoring systems that ensure geometry-aware agents perform reliably in production.

This position offers the opportunity to shape how 3D AI models integrate into agent decision-making pipelines. You'll work closely with applied scientists to productionise breakthrough research whilst building robust systems that handle the unique challenges of geometric data in mission-critical applications.

Your technical focus:

• Architect inference pipelines for 3D vision models handling diverse data types (CAD, mesh, point cloud)
• Build monitoring systems that meaningfully evaluate model performance on real-world, messy geometric data
• Create robust deployment infrastructure scaling across multiple 3D tasks: segmentation, classification, correspondence, and generation
• Implement model lifecycle management supporting both discriminative and generative 3D capabilities
• Design observability frameworks enabling continuous production assessment of 3D model performance

Your background should include:

• 3-10+ years industry experience as an ML Engineer / Computer Vision Engineer
• Proven experience deploying models, especially vision or 3D models
• Strong Python and PyTorch skills with engineering discipline around testing and performance profiling
• Experience with observability tools and ML monitoring best practices
• Deep understanding of challenges specific to deploying 3D models (geometric artifacts, mesh quality, robustness)

Valuable additional experience:

• Working with CAD systems, robotics stacks, or AR/VR environments
• Agent frameworks, planning pipelines, or LLM-integrated systems
• 3D data evaluation methodologies and debugging tools
• Any experience in 3D tools such as WebGL, Three.js, or Blender scripting for 3D visualisation would be useful but not essential.

You'll be establishing the infrastructure foundation for an entirely new capability domain, with high ownership and responsibility for defining production standards and deployment strategies.

Package includes:

• Competitive salary: $180,000-$240,000 
• Performance bonus up to 20%
• Medical, dental, and vision coverage
• 401k with up to 3% company match (after 3 months)
• 20 vacation days, 10 sick days, and flexible working arrangements

Based in SF Bay Area or Miami, working alongside a research team that values practical impact and technical excellence.

You must have valid right to work in the US without sponsorship (US Citizenship or Green Card).

If building the systems that make breakthrough 3D AI research truly useful appeals to you, we'd love to discuss this opportunity. All applicants will receive a response.

Ready to pioneer deep generative modeling for real-time video synthesis?

Join a pioneering startup developing the foundation layer for the next big AI unlock, video behaviour and naturalness of conversation in video generation. 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 generative modelling research. 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 visual generation for embodied intelligence. Their beta platform already demonstrates sophisticated real-time video generation systems with advanced generative models creating natural facial expressions and body movements.

The company is building foundational generative technology that creates dynamic visual content from multimodal inputs, developing systems that generate realistic human-like expressions and movements. Their research sits at the intersection of computer vision, deep generative modeling, and real-time video synthesis.

Your focus:

• Conduct cutting-edge research in deep generative modeling for vision and video generation
• Develop sophisticated generative models for facial expressions, body dynamics, and full avatar synthesis
• Create novel architectures using diffusion models and flow matching for video generation
• Build real-time generative pipelines for dynamic visual content creation
• Advance state-of-the-art techniques in multimodal generative modeling
• Collaborate with engineering to productionise generative models 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 advanced generative architectures for video synthesis. The focus is on creating high-quality, temporally consistent video generation that can power natural embodied agents, emphasising real-time performance and visual fidelity.

Requirements:

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

Nice to have:

• Industry experience deploying generative models in real-time applications
• Background in 3D generation, neural rendering, or Gaussian splatting
• Experience with video generation frameworks and temporal consistency methods

Environment: You'll join a distributed team working primarily in Pacific Time zones, collaborating with specialists in generative modeling, computer vision, and video synthesis. The culture emphasises high ownership, velocity with purpose, and collaborative problem-solving in a fast-moving research environment.

Package:

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

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

If you're excited about conducting pioneering research in deep generative modeling for vision while shaping the future of embodied agents, this offers an exceptional opportunity to work on genuinely transformative technology.

Ready to help create the next generation of visual AI?

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.