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.

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.

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.

Want to scale AI Agents through innovative ML infrastructure?

A pioneering AI company is looking for an experienced Engineer to revolutionize how their agent technology is deployed and served. While others follow conventional paths, they're creating new approaches to agent-specific serving challenges.

Short term, you'll focus on cloud deployment and performance optimization, enhancing their current infrastructure. Long term, you'll help design and build proprietary frameworks that challenge the status quo of model serving.

What You'll Do:

• Architect and improve cloud-based deployment systems 
• Create efficient solutions for concurrent model serving
• Lead the transition from Open Source and third-party tools to custom frameworks
• Drive innovation in model compression and performance
• Design new approaches to large-scale model deployment

You Should Have:

• Advanced degree in Computer Science or related field
• Strong background in MLOps or Model Inference
• Experience scaling AI models in production
• Python expertise and interest in systems programming
• Track record of solving complex deployment challenges

Bonus Points For:

• LLM model serving such as vLLM or similar
  Building custom serving solutions
• Knowledge of GPU optimization
• Experience with large language models
• Background in high-performance computing

You'll join a world-class team pushing the boundaries of what's possible with AI agents. Work remotely (EU/US East Coast) or hybrid from their London office.

This role is perfect for someone who:

• Enjoys tackling unprecedented technical challenges
• Thinks creatively about infrastructure problems
• Values practical solutions while innovating for the future
• Thrives in fast-paced, research-driven environments

Compensation is highly competitive, reflecting the senior nature of the role.

Ready to help define the future of AI infrastructure? Contact Marc at Techire AI to learn more. All applications will receive a response.

Looking to Push the Boundaries of Safe, Superintelligent AI Agents?

A pioneering AI company is seeking a Research Scientist to help develop sophisticated multi-agent systems that enhance human capabilities in complex tasks.

Backed by substantial funding and led by an exceptional founding team, they're developing advanced AI agent architectures incorporating multi-agent reinforcement learning, environment navigation, decision-making systems, LLM agents, planning, and memory frameworks.

As a Research Scientist specializing in reinforcement learning and multi-agent systems, you'll join at a pivotal time as they scale to over 100 team members. You'll work on:

• Advancing multi-agent reinforcement learning systems
• Developing novel approaches to agent coordination
• Designing sophisticated planning and memory architectures
• Contributing to the development of proprietary large language models
• Ensuring safety and reliability in agent systems

Requirements:

• PhD in Computer Science, Machine Learning, or related field
• Strong publication record in reinforcement learning and multi-agent systems
• Experience with large language models and agent architectures
• Track record of novel contributions to AI safety and reliability
• Expertise in designing and implementing complex AI systems

The role offers flexibility with remote work options in EU time zones (East Coast US also considered) or the opportunity to work from their London office.

The package reflects the senior nature of the role, with base salaries ranging from £150,000 to £275,000 (negotiable for industry-leading researchers), plus competitive equity and comprehensive benefits.

If you're passionate about shaping the future of safe, intelligent AI agents, apply now. All applications will receive a response.