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.

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.

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-$250k 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?

Lead AI research that shapes how AI evaluates AI

Want to pioneer AI supervision systems that ensure powerful models can be safely trusted? This leadership role offers a rare chance to solve one of AI's most critical challenges: making AI systems that can effectively evaluate other AI.

You'll join a well-funded startup backed by top Silicon Valley VCs and led by a team with elite ML research backgrounds from FAIR, Meta Reality Labs, and quant finance. Their technology is already trusted by OpenAI, HP, and Fortune 100 companies across education, finance, and healthcare.

As Head of AI, you'll lead a team building cutting-edge evaluation systems that leverage memory, long-context reasoning, and multimodal capabilities. Your research won't just advance the field – it will be immediately implemented in products that solve real enterprise AI safety challenges.

The team has published at top ML conferences (NeurIPS, EMNLP, ACL) and developed models and benchmarks used by leading AI companies worldwide. Their evaluators already outperform OpenAI's by 18% in hallucination detection.

Your focus:

• Lead a research and ML engineering team developing state-of-the-art AI supervision systems
• Solve open research problems in evaluation, explainability, and robustness
• Set research vision alongside the CTO and establish rigorous research processes
• Guide development of novel benchmarks for SOTA AI systems
• Represent the company through publications, speaking, and industry relationships
• Build and grow a world-class technical team

You should have:

• PhD in Computer Science, Mathematics, Statistics, Linguistics or related field
• Strong publication record at top AI conferences (NeurIPS, ICML, EMNLP, ACL)
• Experience conducting empirical NLP research in academic or industry settings
• Deep knowledge of transformer architectures and evaluation frameworks
• Experience training language models in applied or research contexts
• Ability to communicate complex technical concepts across different audiences

The package:

• Competitive salary ($300K-$350K base) 
• Meaningful equity in a well-funded startup
• Performance bonus
• Full health, dental and vision coverage
• 401k plan
• Unlimited PTO
• Regular global team off site days

Location preference for NYC or SF, with flexibility for exceptional candidates.

If you're passionate about ensuring advanced AI systems can be effectively supervised and evaluated, this role offers the chance to make a significant impact on the future of AI safety and deployment.

Shape the future of agentic AI through cutting-edge data strategy

Want to pioneer next-generation data techniques for advanced AI systems? This role combines frontier model research with practical implementation at one of Europe's most ambitious AI startups.

You'll join a rapidly growing AI Data team developing cutting-edge data-centric approaches that enhance LLMs, VLMs, and Action Models. This isn't just about collecting data – it's about transforming how AI systems learn and operate through synthetic generation, model distillation, and preference alignment.

Founded with a clear mission to push the boundaries of superintelligent agentic AI, this well-funded startup ($200M raised) is assembling world-class talent focused on both advancing capabilities and ensuring responsible development. Their approach is comprehensive – building proprietary technology from data to models, focusing on language, multimodal, and vision systems with superior performance and cost-effectiveness.

As an Applied Engineer focusing on Data Research, you'll develop sophisticated data strategies that directly impact frontier AI systems:

• Generate and augment synthetic multimodal datasets for VQA, agent behaviours, and virtual navigation
• Apply model distillation techniques to optimise large-scale models for edge deployment
• Design evaluation frameworks to measure improvements across multiple domains
• Lead research into aligning data with human and AI preferences
• Collaborate with cross-functional teams to integrate data-driven solutions

This role offers rare access to significant compute resources, with a massive GPU cluster that enables cutting-edge work. You'll be joining at a pivotal stage where your contributions will shape core technology and direction.

Requirements:

• Strong Python programming skills covering parallel computing, system design, and large-scale deployments
• Experience developing multimodal data pipelines
• Background in training and deploying LLMs, VLMs or PyTorch models
• MSc or PhD in machine learning, computer vision, NLP, or related field
• Deep understanding of training and evaluation paradigms for multimodal models
• Effectiveness in fast-changing environments

Nice to have:

• Experience with agent-specific data pipelines
• Background in multimodal human annotation platforms
• Document understanding/OCR expertise
• Synthetic data generation experience (particularly multimodal)

You'll have flexibility to work from New York, London, or remotely within European or US East Coast time zones. For those based in cities with offices, hybrid arrangements are available.

Your package includes a highly competitive salary ($200,000-$350,000 depending on experience) plus significant equity with strong upside potential.

If you're passionate about advancing AI through innovative data approaches and want to make a lasting impact on agentic systems, we'd love to hear from you. All applicants will receive a response.

Create agentic AI for industries where decisions matter: from healthcare to aerospace. Oh, and you’ll have the compute power train large models to solve this challenge.

Your role as Applied Scientist is to build next-generation AI agents solving real problems in regulated STEM fields. From Healthcare to Aerospace. You’ll train large transformer models and work on reasoning and agentic ai to create secure, explainable agentic AI systems for regulated environments.

You'll be joining a top team, ex-big tech and start-up execs and a founder who is a successful entrepreneur with billion-dollar+ exits. This company is tackling the significant architectural, security, and ethical challenges of current AI systems. They've also raised $ 20 million and are already working with companies in industries where standard AI approaches fall short.

Your focus:

• Applied research from research to data to model fine-tuning & training and evals.
• Training (pre & post-training) and fine-tuning Large Language Models (text and multimodal) specifically for complex industry workflows.
• Creating systems with strong reasoning and explainability capabilities
• Working with complex datasets (proprietary, customer, and synthetic)
• Implementing supervised fine-tuning and reinforcement learning techniques
• Collaborating with engineering teams to pass off model deployment

The ideal candidate has:

• Hands-on experience training LLMs from scratch
• Deep understanding of transformers
• Experienced in Applied Research
• Strong Python and PyTorch skills
• Experience with NLP or multimodal models (computer vision backgrounds considered if you've worked with large transformer models)
• Track record of building real AI products with measurable impact

They offer:

• Abundant compute resources for training large models
• Salary ranges from $200k-$250k for experienced hires, plus up to 20% performance bonus
• Significant share package
• Healthcare (medical, dental, vision)
• 401k
• 20 vacation days and flexible working hours
• Relocation package.

You'll join a team that values clear communication, hands-on building, and a no-ego culture. The research team is small now but growing to 15-20 members within the next year, giving you significant influence on direction and approach – giving the chance to put your stamp on truly Agentic systems.

You’ll need to be based in Miami or Fort Lauderdale, the work arrangement is hybrid. Generous relocation package on offer if you are relocating to Florida.

You must have eligibility to work in the US and valid right to work. At this time, visas cannot be sponsored. 

If solving unique technical challenges in an ego-free environment with strong resources appeals to you, reach out for a confidential conversation. Everyone will receive a response.

Join a Research Team in SOTA Multimodal AI

Are you ready to shape the future of generative AI? We’re looking for a passionate Researcher/Scientist to join a team pushing the limits of foundational multimodal models.

You’re an expert in complex AI systems with a track record of impactful research publications in at least one of these areas:

1 - Vision Generation: Video, image, 3D, or large vision models (LVMs)
2-  Generation: Audio, speech/TTS, or music
3- Text Generation: Natural language generation (NLG) or large language models (LLMs)

Your expertise lies in generative models—researching, building, and training them from the ground up. You thrive on solving tough challenges, whether it’s training and fine-tuning Diffusion models, optimizing performance of LVMs, or inventing new techniques to push latency/inference to the next level. Naturally, you’re a Python pro and fluent in deep learning frameworks like PyTorch or TensorFlow. 

What You’ll Do

You’ll join a team of innovators tackling groundbreaking research that’s redefining multimodal AI. Your work won’t just sit in a lab—it’ll ship to millions of users, powering a product that’s accelerating the field. This is your chance to see your ideas come to life at scale.

Who You’ll Work With

You’ll collaborate with a seasoned crew, including alumni from DeepMind, OpenAI, NVIDIA, and Meta. Backed by top-tier VCs and fueled by fast-growing revenue, this team has the resources and ambition to make waves—and they’re just getting started.

What You’ll Get

Salary: $220k–$350k base, plus a generous equity packageBenefits: Comprehensive healthcare (health, dental, vision), unlimited PTO, and more

Location: San Francisco preferred; remote possible for standout candidates (those at top tier AI labs or industry leading published authors)

If you’re ready to leave your mark on the future of AI, apply now or reach out to Marc Powell at techire.ai for immediate consideration.

Passionate about building frontier language models that power autonomous agents?

Join a forward-thinking AI venture creating the technology that will reshape how we interact with machines. Their mission? Developing superintelligent agents that handle complex tasks.

This role puts you at the center of model development, designing and training the enormous language models that form the foundation of their agent architecture. You'll help forge new paths in AI by crafting models specifically engineered for agent-based applications.

Day to day, you'll:

• Craft and refine massive data pipelines for model training
• Enhance distributed training infrastructure
• Apply cutting-edge research to boost model capabilities
• Present findings to both technical teams and stakeholders
• Track and implement breakthroughs from the research community

Ideal candidates bring:

• Hands-on experience with major deep learning frameworks
• Track record training or optimizing large language models
• Knowledge of distributed systems for AI workloads
• Strong engineering skills
• MS or PhD in a relevant technical field

Bonus points for:

• Research published in prestigious ML conferences
• Experience with large-scale data processing
• Knowledge of vision-language models or action models 
• Background in model efficiency techniques

Choose between fully remote work across European or East Coast US time zones, or hybrid arrangements if you're based near their London office. 

You'll be welcomed into a diverse team of top researchers and engineers united by their commitment to building powerful yet responsible AI.

Want to help shape the core technology driving the next wave of AI advancement? This opportunity connects you directly to that mission.