Want to work with AI agents used for good?

Join a well-funded AI company developing next-generation foundation models specifically for healthcare. With over $250 million backing from top-tier investors, they're creating agents, foundation language models, and real-time empathetic and nartural conversational AI that prioritise safety and medical accuracy.

You'll join a world-class research team comprised of ex-researchers from Microsoft, Meta, NVIDIA, Apple, Stanford, Johns Hopkins, and HuggingFace. This role offers the opportunity to work on AI technology that could transform healthcare outcomes for millions worldwide.

Your focus:

• Developing and improving LLMs for healthcare applications, directly contributing to agent architecture and conversational AI systems
• Implementing advanced post-training techniques including instruction tuning and RLHF
• Building systems capable of real-time patient interactions with medical-grade accuracy
• Advancing multilingual capabilities for global healthcare accessibility
• Researching continual learning approaches that evolve through patient interactions
• Collaborating with researchers from top universities and leading tech companies

Your expertise:

• Hands-on experience training multi-billion parameter large language models
• Strong background in NLP with deep understanding of transformer architectures
• Experience as an Applied researcher with excellent Python and PyTorch coding skills
• Expertise in reinforcement learning, RLHF, LLM post-training, and supervised fine-tuning
• Experience with large-scale data processing and distributed computing

Nice to have:

• Healthcare or life sciences background
• Publications at top-tier AI conferences
• Experience with multimodal AI systems

Your package:

• Base salary: $200,000-$350,000 (based on experience)
• Stock package
• Comprehensive benefits including healthcare, dental, and vision
• 401k with company contributions

Based near Palo Alto, CA with strong preference for on-site collaboration.

This isn't just another AI research role - it's the chance to build technology that could fundamentally improve healthcare delivery globally. Your work will contribute to creating AI systems that assist with patient care and improve healthcare accessibility.

Ready to help shape the future of healthcare through AI? Apply today. All applications will receive a response.

Ready to pioneer the speech intelligence behind the next generation of embodied AI?

Join a pioneering startup developing foundational technology for natural conversation in embodied agents. You'll advance the speech systems that power avatars with authentic behaviours, real-time expression, and conversational intelligence that handles interruptions and turn-taking just like humans.

This Lead Research Scientist role focuses on advancing real-time speech systems for interactive avatars. You'll develop full-duplex dialogue models and speech-to-speech architectures that enable natural conversational flow, interruption handling, and emotional expression.

Founded by ex-Googlers, they're building proprietary behaviour models that learn from two-way interactions, creating systems where speech timing, prosody, and contextual responses work in harmony with facial expressions and physical behaviours to drive authentic embodied intelligence.

Your focus:

• Research & develop full-duplex speech systems with natural interruption handling
• Develop expressive voice models with controllable prosody and timing
• Build speech-to-speech architectures preserving identity and emotion
• Create real-time audio generation systems for conversational avatars
• Publish research while deploying systems in production
• Collaborate across teams integrating speech with visual behaviour

Requirements:

• PhD in Speech, Machine Learning, or related field
• First-author publications at top conferences (Interspeech, ICASSP, NeurIPS, ICLR, etc)
• Expertise in text-to-speech, speech-to-speech models, or voice cloning
• Large-scale training experience
• Experience in prosody modelling or real-time audio generation

Nice to have:

• Experience with full-duplex speech research
• Speech-visual alignment expertise (lip sync, expressions)
• Real-time audio deployment optimisation

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.

Ready to make AI conversations feel authentically human?

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.

Build the foundational models that will give AI agents true 3D understanding

Want to solve the fundamental challenge of how AI systems perceive and reason about 3D geometry?

This Applied Scientist role puts you at the forefront of creating perception capabilities for the next generation of agentic AI systems. You'll see your models introduced into agentic workflows, solving complex challenges in agentic AI for industrial applications.

You'll be joining a well-funded startup developing AI agents for advanced design and manufacturing workflows. Your work will bridge the gap between the physical world and intelligent reasoning systems, creating models that understand CAD data, meshes, and point clouds at a level that enables autonomous decision-making.

This role offers the rare opportunity to build 3D computer vision capabilities from the ground up. You'll be establishing an entirely new domain within the research team, with significant autonomy to define evaluation strategies, model objectives, and technical direction. Your models will form the perception backbone that enables agents to truly understand and manipulate the 3D world.

Your technical challenges:

• Build models that understand diverse 3D data types (CAD, mesh, point cloud) and learn transferable representations across formats
• Handle messy, lossy, or incomplete real-world data - moving beyond clean synthetic geometry to tackle industrial reality
• Scale training across multiple 3D tasks: segmentation, classification, correspondence, and eventually generation
• Create evaluation pipelines that meaningfully assess model performance and enable continuous production monitoring
• Work toward a foundational 3D model supporting both discriminative and generative tasks, integrated into broader agentic AI architecture

Your expertise should include:

• Deep specialisation in 3D computer vision (ideally including a PhD in Computer Vision)
• Strong knowledge of modern 3D architectures (PointNet++, MeshCNN, 3D Gaussian Splatting, diffusion models, VLMs)
• Proven ability training large-scale deep learning models with PyTorch
• Solid applied research skills - can implement novel architectures from papers and make them work in practice
• Experience with multimodal or vision-language model development

Nice to have:

• Background working with CAD data or industrial design workflows
• Experience in complex topics such as robotics, autonomous driving, or AR/VR with 3D perception focus
• Familiarity with SLAM, pose estimation, or differentiable rendering

You'll join a research team that values ownership and rapid iteration, with the resources to pursue ambitious technical goals. The company provides abundant compute resources and the freedom to explore foundational approaches whilst ensuring practical impact.

Package includes:

• Base salary: $200,000 (mid/senior) - $250,000 (Staff - negotiable)
• Performance bonus up to 20%
• Medical, dental, and vision coverage
• 401k with up to 3% company match
• 20+ vacation days

You'll need to be based in SF Bay Area or Miami, with a collaborative team environment that encourages innovation and technical excellence.

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

If you're excited about creating the 3D perception capabilities that will power the next generation of intelligent agents, we'd love to hear from you. 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.

Build the ML infrastructure that powers cutting-edge AI across multiple domains

Ready to architect MLOps systems from the ground up for a fast-growing AI team? This greenfield opportunity offers complete autonomy to design and build training pipelines for LLMs, computer vision models, and other deep learning architectures that will power next-generation AI applications.

You'll join a well-funded startup ($20M+ raised, with a new round expected this year) developing production-grade AI solutions across regulated industries including healthcare, aerospace and manufacturing. Founded by a successful entrepreneur with a previous billion-dollar exit, they're already partnering with Fortune 100 and 500 clients where standard AI approaches fall short.

This role offers exceptional technical ownership - you'll build their ML infrastructure from current basic tooling to production-scale systems that support their rapidly expanding applied AI team. They have significant GPU resources with substantial budget growth expected. As the team scales to ~20 people within the year, there's high potential for you to lead future MLOps hires.

The challenge is substantial: creating infrastructure that supports training across multiple modalities - from LLMs to computer vision models. You'll work with large compute resources and have complete autonomy to select and implement the tooling that will define how the team operates for years to come. Your initial focus will be establishing robust training and evaluation pipelines, then scaling to enterprise-grade data workflows with versioning, monitoring, and automated deployment systems.

Your focus:

• Build training and evaluation pipelines for LLMs, vision models, and other deep learning architectures
• Design distributed training systems on multi-GPU clusters across model types
• Create scalable data pipelines, versioning systems, and model checkpointing workflows
• Implement model serving infrastructure with tools like vLLM, Triton, and TorchServe
• Establish comprehensive monitoring, experiment tracking, and reproducibility systems
• Support a rapidly growing applied AI team with robust CI/CD workflows for ML systems

You should have:

• 3+ years building MLOps infrastructure or ML systems in production environments
• Hands-on experience with training pipelines for deep learning models (LLMs, CNNs, transformers)
• Strong expertise with AWS and Kubernetes (mandatory requirements)
• Proficiency with Python, PyTorch/TensorFlow, and distributed training libraries
• Experience with model tracking tools like Weights & Biases or MLflow
• Understanding of modern ML architectures across multiple domains

Nice to have:

• Experience with LLM inference tools (vLLM, SGLang, RayServer)
• Ray experience for distributed computing
• Knowledge of mixed-precision training, quantisation, and model optimisation
• Computer vision workflow experience
• Data versioning tools (DVC, LakeFS)
• Early-stage startup experience

You'll receive:

• Competitive base salary: circa $250K (based on experience)
• Significant stock package in a fast-growing company
• Access to substantial GPU budget with expected growth
• Healthcare (medical, dental, vision) and 401k with matching
• 20 vacation days plus flexible working arrangements

You must be based in SF Bay Area or Miami (relocation is provided to Florida only). At this time we can only consider US citizens or green card holders.nd.

Ready to build the infrastructure that powers the future of production 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.

Build agentic AI for industries where decisions truly matter - from healthcare to aerospace

Ready to create AI agents that solve real-world challenges in regulated environments? Join a well-funded startup developing secure, explainable AI systems for industries where standard approaches fall short.

You'll work as an AI Engineer in the Applied Science team, taking AI models from research to production and integrating agentic AI systems into real applications. This engineering-focused role involves building and deploying AI automation tools that tackle complex industry workflows across healthcare, aerospace, defence, and manufacturing.

Founded by a successful entrepreneur with previous billion-dollar exits, this company has raised $20M+ and is already partnering with Fortune 500 clients in regulated STEM fields. They're assembling a world-class team to create the next generation of secure, transparent AI agents.

The role offers unique technical challenges in agentic systems for enterprise environments, with access to significant compute resources and the opportunity to shape the direction of a fast-growing team in a no-ego culture focused on building working solutions.

Your focus:

• Develop AI-driven reasoning agents and frameworks for automating complex tasks
• Build and optimise RAG (Retrieval-Augmented Generation) pipelines
• Distill and fine-tune AI models to improve reasoning, automation, and decision-making
• Deploy AI models into scalable, production-ready systems using Python and cloud infrastructure
• Collaborate with researchers to operationalise AI advancements into real applications
• Work with complex datasets (proprietary, customer, and synthetic data)

You should have:

• Proven experience building and deploying AI applications (ideally in a startup or fast-moving environment)
• Hands-on expertise with LLMs and agentic frameworks (AutoGen, CrewAI, LangChain, DSPy, or Haystack)
• Strong background in AI-powered automation and orchestration workflows
• Experience with vector databases and retrieval systems (LlamaIndex, FAISS, Pinecone, Weaviate)
• Solid coding skills in Python and familiarity with cloud deployment tools (AWS, GCP, or Azure)

Nice to have:

• MLOps experience and production ML system deployment
• Experience with fine-tuning AI models

You'll receive:

• Competitive base salary: $160K-$230K (negotiable based on experience)
• Up to 20% performance bonus
• Significant options package
• Healthcare (medical, dental, vision) 
• 401k with up to 3% match 
• 20 vacation days plus 10 sick days with flexible working hours
• Relocation allowance for moves to Florida

You'll be already be based in SF Bay Area or willing to relocate to Miami, Florida, with relocation support provided. The team values clear communication, hands-on building, and collaborative problem-solving in an environment where your work directly impacts the product.

This is an ideal opportunity for an ML Engineer who has built AI applications before and wants to be part of a small, fast-moving team tackling autonomous workflows that solve real problems in mission-critical environments.

Ready to help shape computing intelligence that amplifies human innovation? All applicants will receive a response.

Pioneer groundbreaking research in AI agentic supervision

Want to develop the world's first agentic AI systems that can autonomously supervise and evaluate other AI? This Research Scientist role offers the chance to tackle fundamental challenges in AI supervision, red teaming, and automated evaluation at an unprecedented scale.

You'll join a company pioneering intelligent systems that evaluate advanced AI applications. Their technology, trusted by OpenAI, HP, and Fortune 100 companies, represents the cutting edge of scalable AI oversight. Despite being well-funded with $20M in backing, they're already generating significant ARR - proving real market demand for their solutions. Their evaluators outperform AI industry leaders internal solution by 18% in hallucination detection, and they've developed industry benchmarks used across multiple sectors.

The role focuses on research (50%) developing state-of-the-art systems for autonomous AI supervision, pushing beyond traditional approaches to create truly agentic evaluation frameworks. You'll conduct SOTA research, fine-tune LLMs, implement novel algorithms, conduct groundbreaking research on red teaming, and design experiments that advance the field of automated AI oversight. Here, you'll publish with the team in conjuction with top AI research labs and academic organisations, the role is 50% research and 50% implementation. 

The ideal candidate has:

• Strong experience in Applied AI NLP research
• Publications at leading AI conferences (NeurIPS, ICML, EMNLP, ACL, ICLR)
• Experience fine-tuning LLMs (must-have)
• Deep understanding of transformer architectures and evaluation metrics
• Big Tech experience (highly desirable)
• Experience in evals, LLM as judges, or red teaming

The company works with both startups and Fortune 100 enterprises. Their team has published at top ML conferences and built AI products at leading tech companies.

This role offers competitive compensation ($200k-$300k base - negotiable), significant stock options, full benefits, 401k, and unlimited PTO. Location preference for San Francisco Bay Area. Relocation assistance available. Remote considered for industry-leading researchers in evals.

Interested in pioneering the future of autonomous AI supervision?