Machine Learning Engineer

Hyperbound is building the Revenue Activation Platform for sales, using machine learning models that support roleplay, scoring, and coaching. As a Machine Learning Engineer, you will take ownership of models from training and fine-tuning through deployment, with a focus on keeping performance stable in production.

Role Focus

You will work primarily on fine-tuning and deploying open source models, including scenarios where models need to run on-device to meet customer latency or privacy requirements. A key part of the role is establishing evaluation frameworks and benchmarks to verify whether model changes lead to improved outcomes.

Responsibilities

• Own your models end to end, covering training, evaluation, deployment, and ongoing operation in production.
• Fine-tune and run open source models in production environments.
• Push models on-device when customer constraints require specific latency or privacy characteristics.
• Build evaluation frameworks, benchmarks, and regression suites to determine whether changes improve results.
• Build and ship the models powering Hyperbound roleplay, scoring, and coaching products, including the complete lifecycle from training and fine-tuning through production rollout and maintenance.
• Fine-tune and deploy open source models where they provide more control over cost, latency, and model capabilities.
• Collaborate closely with the founders and engineering team, with direct input into what you build next.

What Hyperbound Is Building

Hyperbound is the Revenue Activation Platform and agentic operating system for sales. Rather than only recording what happens on calls, the platform changes what happens next by turning real selling behavior into targeted roleplays, coaching, and workflow changes that improve reps without adding management overhead.

Ownership and Equity

• Full model ownership across training, evaluation, deployment, and post-deployment operations.
• Compensation includes meaningful equity, with real secondary opportunities.

Work Location and Schedule

• Onsite in San Francisco, CA.
• In the office five days a week.

Compensation and Benefits

• Compensation: USD 260,000 to 300,000 per year, plus meaningful equity, based on experience.
• Medical, dental, and vision coverage.
• 401k.
• Commuter and parking benefits.
• Unlimited PTO.
• Free lunch and dinner in the office.

Interview Process

The process is designed to move quickly, typically spanning an intro call, a technical conversation with the team you would work with, and a final discussion with the founders. The timeline is 1 to 2 weeks from first conversation to offer.