Interested in advancing how agents and LLMs learn from feedback in realistic environments?

You’ll be joining a research-driven AI company building reinforcement learning simulation environments for agents and large language models, with a focus on post-training, evaluation, and scalable supervision. 

Their tools are already used in production by leading AI labs and enterprises and due to demand they are growing fast.

As a Research Scientist, you’ll work hands-on on fundamental problems spanning LLM post-training, RL environments, and agentic evaluation. Your work will shape core methods and benchmarks, and you’ll see your research deployed into production systems. The team actively publishes and collaborates with external research labs, with recent work appearing at ACL and NeurIPS.

What you’ll do

• Conduct research on LLM post-training methods (RLHF, RLAIF, RLVR)

• Design and build realistic RL simulation environments for agents

• Develop agentic evaluation and supervision frameworks

• Create and maintain benchmarks for emerging AI capabilities

• Collaborate with engineers to take research from idea to deployed systems

What you’ll bring

• Experience in applied research in reinforcement learning, LLM post-training, or agent-based systems

• Strong understanding of transformer architectures and LLM fine-tuning

• Ability to translate research ideas into working, production-ready systems

Nice to have

• Publications at top-tier venues (NeurIPS, ICML, ACL, EMNLP)

• Experience working on evaluation, safety, or oversight for advanced AI systems

• Prior work on large-scale training or simulation environments

SF-based. Compensation up to $300k base (flexible, DOE) plus equity, unlimited PTO, and benefits.

Interested in working on the foundations of AI training, evaluation, and safety—while publishing high-quality research that ships?

All applications 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.