ML Engineer
About the Role
As a Machine Learning Engineer, you’ll push the frontier of post-training for large language models from supervised fine-tuning to advanced reinforcement learning to train powerful agents capable of complex, end-to-end reasoning and action.
You’ll work side-by-side with our researchers to rapidly iterate on alignment strategies, implement state-of-the-art training algorithms, and run large-scale experiments that directly improve our production models.
If you love making models smarter, safer, and more capable, and want to work at the cutting edge of LLM agent training, this role is for you.
Responsibilities
Post-train SOTA LLMs on query answering by using the latest in supervised and reinforcement learning techniques
Own the full stack data, training, and eval pipelines required to post-train LLM models
Deliver Sonar models that provide SOTA query answering
Work closing with engineering teams to integrate Sonar models into our product
Qualifications
Proven experience with large-scale LLMs and Deep Learning systems
Strong programming skills; versatility is a plus
Self-starter with a willingness to take ownership of tasks
Passion for tackling challenging problems
Bonus
Experience training agentic LLMs with end-to-end reinforcement learning
Prior research experience
What makes us interesting
Small, elite team of ex-founders, researchers from top AI Labs, top CS grads, and engineers from top companies
True ownership You will not be blocked by bureaucracy, shipping meaningful work within weeks rather than months
Serious momentum We're well-funded by top investors, moving fast, and focused on execution
What we do
Ship consumer products powered by cutting-edge AI research, and
Build infrastructure that facilitates research and product, and
Innovate cutting-edge research that will open up new consumer product forms
The Details
Full-time, onsite role in Menlo Park
Startup hours apply
Generous salary, with additional benefits to be discussed during the hiring process
Average salary estimate
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