Machine Learning Researcher

Help us push the boundaries of what's possible in LLM post-training. If you love training models, exploring new architectures, running experiments, and turning research insights into products that ship, we'd love to meet you.

trains and hosts specialized language models for companies who want frontier-quality AI at a fraction of the cost. The models we train match GPT‑5 accuracy but are smaller, faster, and up to 90% cheaper. Our platform handles everything end‑to‑end: distillation, training, evaluation, and planet‑scale hosting.

You will be responsible for conducting research into experimental models, training systems, and modalities to create novel products for our customers. Your work will span from exploring new architectures and learning methods to optimizing latency and efficiency, with the goal of delivering better models to customers.

• Research and experiment with new model architectures to improve quality, efficiency, or capability
• Explore methods to decrease inference latency and improve serving efficiency
• Run experiments with new learning methods, including novel approaches to SFT, RLHF, DPO, and other post‑training techniques
• Perform reinforcement learning research to improve model alignment and capability
• Develop and improve our distillation pipeline for training high‑quality models from frontier teachers
• Train models for clients and run evaluations to validate research findings in production settings
• Create robust benchmarks and evaluation frameworks that ensure custom models match or exceed frontier performance
• Stay current with ML research and identify techniques that can improve our platform
• Collaborate with applied engineers to bring successful research into production systems
• Document findings and share knowledge with the team

• 3+ years of experience training AI models using Py Torch
• Deep understanding of transformer architectures, attention mechanisms, and model internals
• Hands‑on experience with post‑training LLMs using SFT, RLHF, DPO, or other alignment techniques
• Experience with LLM‑specific training frameworks (e.g., Hugging Face Transformers, Deep Speed, Megatron, TRL, or similar)
• Strong experimental methodology, including ability to design, run, and analyze rigorous experiments
• Track record of implementing ideas from recent ML papers
• Experience training on NVIDIA GPUs at scale
• Strong foundation in ML fundamentals: optimization, loss functions, regularization, generalization

• Publications in ML venues
• Experience with model distillation or knowledge transfer
• Experience with LLM speed optimization techniques
• Familiarity with vision encoders, multimodal models, or other modalities
• Experience with distributed training and infrastructure at scale
• Contributions to open‑source ML projects

We offer competitive compensation, equity in a high‑growth startup, and comprehensive benefits. The base salary range for this role is $250,000 – $350,000, plus equity and benefits, depending on experience.

is an equal opportunity employer. We welcome applicants from all backgrounds and don't discriminate based on race, color, religion, gender, sexual orientation, national origin, genetics, disability, age, or veteran status.