Machine Learning Engineer

Hyperbound•San Francisco, CA

5d•Onsite

About The Position

We are looking for a Machine Learning Engineer to join our team. This role involves owning models end-to-end, from training through production. You will focus on fine-tuning and deploying open-source models, pushing models on-device, and building evaluation frameworks. This is a challenging but exciting role where you will work alongside a dedicated team.

Requirements

Experience owning models end-to-end: training, evaluation, and deployment.
Proficiency in fine-tuning and deploying open-source models.
Experience with on-device model deployment, quantization, and distillation.
Skilled in building evaluation frameworks, benchmarks, and regression suites.
Ability to work in an office environment five days a week in San Francisco.
Willingness to work in a fast-paced environment with high expectations.

Nice To Haves

Experience in the Revenue Activation Platform domain.
Familiarity with agentic operating systems for sales.
Experience with sales roleplay, coaching, or workflow optimization.

Responsibilities

Build and ship the models underneath Hyperbound's roleplay, scoring, and coaching products.
Own the full lifecycle of models, from training and fine-tuning through deployment and maintenance in production.
Fine-tune and deploy open-source models to optimize for cost, latency, or functionality.
Implement models on-device to meet customer latency or privacy requirements, involving quantization and distillation.
Develop evaluation frameworks, benchmarks, and regression suites to ensure model performance and identify improvements.
Collaborate closely with founders and the engineering team, contributing to product development decisions.