--- title: 'Machine Learning Engineer at Hyperbound' canonical: 'https://feeny.ai/job/machine-learning-engineer-hyperbound-san-francisco-cbq0dd9m4ft7' type: 'job' last_seen: '2026-09-09' --- # Machine Learning Engineer at Hyperbound - **Company:** Hyperbound - **Location:** San Francisco, CA - **Employment:** full-time - **Work type:** onsite - **Posted:** 2026-08-28 - **Last confirmed live:** 2026-09-09 - **Apply:** https://jobs.ashbyhq.com/hyperbound/e58222f2-3835-4107-863c-c68947e48489 ## Job description We’re probably not the right fit for you. ## THE REALITY We're in the office five days a week in San Francisco. We move fast and expect a lot. We’re most effective when everyone is in the same room, thinking out loud, catching each other's mistakes early. You'll own your models end to end, training through production. We trust you to handle that. You'll spend most of your time working fine-tuning and running open source models in production, pushing models on-device, and building the evaluation frameworks that tell us whether a change actually worked instead of trusting our gut. This will probably be one of the hardest jobs you've had. We think it'll also be one of the more exciting ones, and we'll be here right alongside you. Sound exciting? Good. We’re excited too. ## WHAT WE'RE BUILDING Hyperbound is the Revenue Activation Platform, the agentic operating system for sales. We don't just record what happens on a call, we change what happens next, turning real selling behavior into targeted roleplays, coaching, and workflow changes that make reps better without adding a single layer of management overhead. Founded in 2023 out of YC (S23), we're 45 people now, Series A, $18M raised total. Last quarter we doubled headcount, revenue nearly doubled with it, and net revenue retention landed above 300%. Teams at LinkedIn, Workday, and Intel run their sales orgs on us. ## THE ROLE You'll build and ship the models underneath Hyperbound's roleplay, scoring, and coaching products: real systems sitting on real sales calls. That means owning the full lifecycle, from training and fine-tuning through getting a model into production and keeping it working once it's there. You will fine-tune and deploy open source models where they give us more control over cost, latency, or what the model can actually do. Some of it means getting models running on-device, wherever a customer's latency or privacy requirements demand it, with all the tradeoffs around quantization and distillation that come with it. And a good amount of it means building the evaluation frameworks, benchmarks, and regression suites that tell us whether a change actually made things better, before a customer finds out for us. You'll work closely with the founders and the rest of engineering, and you'll have real input into what we build next, not just how we build it. ## THE TEAM We're assembling a cracked team of builders, operators, and hunters. We've hired people from our competition, former co-founders, and early customers who loved the product. The engineers you'd work alongside are builders first. Some have started their own companies. Nobody here is precious about their code, and nobody hides behind "that's not my problem," people just see something broken and fix it. We work hard and we celebrate for real. We’re demoing features we shipped that morning, and the whiteboards get erased and rewritten constantly. You can feel it when a team actually believes in what it's building, and that's very real here. Here's the team in Bali after we raised our Series A: [https://app.ashbyhq.com/api/images/user-content/dc682caf-65e4-456d-8c74-c4a052bd4d85/6bbff623-0db9-4789-85c1-62038d005f9f/bali.jpg] At the same time, this isn't a mattress-under-your-desk startup: plenty of people here have kids, people leave to make dinner, and they come back the next morning and ship. High standards don't require burnout. We've doubled in size since this photo was taken a few months ago: [https://app.ashbyhq.com/api/images/user-content/dc682caf-65e4-456d-8c74-c4a052bd4d85/23f0f291-c351-4ce4-ae7d-d662040fd951/image_large.png] ## OWNERSHIP AND EQUITY You own your models end to end: the training, the eval, the deployment, and everything that happens after. That cuts both ways, and when it works, that's yours too. Equity here is real, with real secondary opportunities, and we genuinely want the people who build this early to end up meaningfully rewarded for it. ## COMPENSATION AND BENEFITS Comp: $260k-$300k+ based on experience, meaningful equity Benefits: medical, dental, vision, 401k Commuter and parking benefits Unlimited PTO Free lunch and dinner in the office ## THE INTERVIEW PROCESS We move fast: an intro call, a technical conversation with the team you'd actually work with, and a final conversation with the founders. We move fast, 1-2 weeks from first conversation to offer. ## EQUAL OPPORTUNITY Hyperbound is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, and we don't discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. ## About Hyperbound ## Company Overview - **One-liner**: Hyperbound is an AI sales coaching platform that turns real sales calls into realistic roleplays and automated actions to improve rep performance and close deals. - **Entity Type**: Private (seed stage; raised $15M as of 2024) - **Headquarters**: Not publicly disclosed (remote‑first culture inferred from Y Combinator profile) - **Founded**: 2023 - **Founders**: Atul Raghunathan (CEO) and an unnamed co‑founder (active founders on Y Combinator) ## Core Business - **Primary industry**: AI‑powered sales coaching / Revenue Activation Platform - **Target customers**: B2B (Enterprise, SMB); revenue teams (sales reps, managers, enablement) - **Mission**: “Revolutionizing sales training with AI – because reps deserve better coaching.” ## Products & Services - **AI Sales Roleplay**: Realistic roleplays built from a company’s actual sales calls, supporting 25+ languages. Reps practice the exact conversations they’re about to have. *(SaaS)* - **Conversation Intelligence**: Automatically captures call transcripts and surfaces insights, but Hyperbound differentiates by turning insights into coaching actions rather than just dashboards. *(SaaS)* - **Kota (AI Agent)**: “Activate” agent that reads calls, emails, CRM signals, and executes automations – flagging risk, assigning coaching, updating CRM, etc. *(SaaS)* - **AI Scorecards**: Customizable scorecards for any sales methodology or messaging framework. *(SaaS)* - **Integrations**: Seamless connection with existing tech stack (CRM, Slack, etc.). *(API/SaaS)* ## Market Standing - **Valuation**: Not publicly disclosed - **Key Metric**: Total funding raised – $15M (Round led by Y Combinator, per Entrepreneur report) - **Notable Investors**: Y Combinator (active batch); further investors not named in available sources - **Growth Signals**: - Used by 40,000+ reps across 40+ countries - Recognized enterprise customers: IBM, LinkedIn, Monday.com, Bloomberg, Vanta, Autodesk, G2 - Hyperbound’s coaching drove $125M+ pipeline influence for Vanta and reduced ramp time by 60% - Team size grew to 30 (as of YC profile, likely early 2025) ## Competitive Advantages - **Enterprise‑grade security**: SOC 2 Type II, GDPR, HIPAA, ISO 27001 certified - **Privacy‑first**: AI models are pre‑trained on proprietary data; customer data is never used for training - **Real call‑based training**: Roleplays are built from actual company calls, not generic scripts - **Localization**: Supports 25+ languages, used by teams in 40+ countries - **Kota automation**: Unique agent that acts on insights to rescue deals, fill CRM, and trigger coaching without manual dashboard digging ## Strategic Focus - Expand enterprise adoption and scale the “Revenue Activation” category - Continue building AI agents (Kota) that automate coaching and deal rescue - Grow global footprint via localization and compliance certifications - Hire across GTM and engineering to support rapid product iteration ## Why Work Here - **Culture**: “No passengers here. You own your work end to end, share meaningfully, and celebrate properly when we win.” (Careers page) - **Pace**: Fast‑moving startup environment where you “define the future of sales” - **Remote policy**: Not explicitly stated, but Y Combinator profile implies remote‑first; most roles likely remote or hybrid - **Perks**: Equity in a well‑funded YC startup; direct impact on a product used by thousands of reps and top enterprises - **Engineering culture**: Emphasis on ownership, end‑to‑end responsibility, and building AI that drives measurable revenue outcomes ## Sources 1. [hyperbound.ai](https://www.hyperbound.ai/) (main site – product, security, customers) 2. [hyperbound.ai/careers](https://www.hyperbound.ai/careers) (culture, open roles) 3. [hyperbound.ai/about-us](https://www.hyperbound.ai/about-us) (company story, FAQ) 4. [ycombinator.com/companies/hyperbound](https://www.ycombinator.com/companies/hyperbound) (founding date, team size, funding mention) 5. [linkedin.com/company/hyperbound-ai](https://www.linkedin.com/company/hyperbound-ai) (team size, industry) ## Other roles at Hyperbound - [Software Engineer, GTM](https://feeny.ai/job/software-engineer-gtm-hyperbound-san-francisco-9m0s080wffq4) — San Francisco, CA - [Enterprise Account Executive](https://feeny.ai/job/enterprise-account-executive-hyperbound-san-francisco-dnxatsn0644z) — San Francisco, CA - [Platform Engineer](https://feeny.ai/job/platform-engineer-hyperbound-san-francisco-ccvsm9tapjre) — San Francisco, CA - [Mid Market Account Manager](https://feeny.ai/job/mid-market-account-manager-hyperbound-san-francisco-7j1nbdavsm5p) — San Francisco, CA - [Full-Stack Software Engineer](https://feeny.ai/job/full-stack-software-engineer-hyperbound-san-francisco-cqrvxsv5z7f9) — San Francisco, CA - [Senior Product Designer](https://feeny.ai/job/senior-product-designer-hyperbound-san-francisco-s5apztw2rx4n) — San Francisco, CA - [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-yuno-europe-qk68kdrz5rgw) — Europe - [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-pangram-labs-brooklyn-e3hhh2tc2855) — Brooklyn, NY - [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-gatik-ai-santa-clara-qj4vvbdeqt4x) — Santa Clara, CA - [Machine Learning Engineer](https://feeny.ai/job/machine-learning-engineer-wynd-labs-remote-whe42v314npy)