Shaped is the fastest path to relevant recommendation and search systems. We help companies turn their behavioral data into truly relevant product and website experiences.

We're a Series A company based in Brooklyn, New York and backed by top investors from Madrona, Y-Combinator, and executives from Meta, Google, Amazon and Uber!

About Shaped

Shaped is the real-time retrieval engine for search, feeds and agents. We are on a mission to power every product and content experience with world-class search and recommendations. 

Shaped is backed by top-tier investors like Y Combinator and Madrona; with executives from Meta, Google, Amazon and Uber. We’re building an elite team to define the future of how users discover what matters most.

We're excited to work with you. Come build the future of AI with us!

About the role

You will be the first point of contact for Shaped’s customers. Shaped’s Sales Development Representatives (SDRs) will reach out to qualified prospects across various channels, qualify leads, and schedule calls with sales team members. Our ideal SDR has a strong understanding of the sales process and excels at finding leads, starting new relationships and setting up the sales team for success. This is your opportunity to join us in-person as an early employee and make a significant impact at a high growth start-up.

What you will do

• Work closely across the GTM team to strategize and execute outreach campaigns that drive pipeline creation and revenue
• Analyze market data and develop strategic approaches to key accounts to raise awareness and generate interest for Shaped
• Craft compelling messaging across channels including email, phone and LinkedIn in conjunction with other stakeholders
• Identify the needs of potential customers and suggest the appropriate path forward 
• Build long-term, trusting relationships with prospects; own the data
• Schedule demos between prospects and sales executives
• Own hand-offs and tracking opportunity account details including use case, purchase timeframes and next steps
• Report weekly, monthly and quarterly metrics

Who you are

• 1+ years of experience (bonus points for a start-up environment!) OR new graduate from a top-school and top-internships
• Proven history of exceeding targets at at high-growth environments
• History of strategic and creative pipeline generation tactics - you are constantly testing and iterating on channels, messaging, and tactics
• Polished written and verbal communication, an entrepreneurial mindset with problem-solving and analytical skills - you know how to hit an SLA
• Excellent at building relationships with prospects and customers - you’re an excellent listener
• Impeccable organizational skills with fine attention to detail
• Collaborative attitude with strong cross-functional skills - you are comfortable sharing learnings with marketing, sales, and engineering teams
• Scrappiness in helping design and operate GTM tech stack (HubSpot, Unify, etc.)
• Bachelor’s Degree

Benefits

⚕️Comprehensive medical, dental, and vision insurance

🏦 Flexible Spending Account (FSA), Health Savings Account (HSA)

🦮 Expert Healthcare Guidance

💵 Retirement savings

🎄 Company holidays each year

🏖️ Unlimited days for personal time each year

🚌 Flex Commuter Benefits

🥤Office is fully-stocked with drinks and snacks to fuel your work day.

🍽️ Staying late? Dinner is on us

Customers typically use Shaped as follows:

1. Connect your data stack, e.g. data warehouse, database or analytics applications
2. Define your engine. This includes your optimization objective (e.g. clicks vs purchases vs shares), item and user catalogs, feature types and model types.
3. Consume your results from our real-time, scalable ranking endpoints
4. Evaluate uplift and model results on our dashboard.

To power all of this, under the hood, we've built a multi-tenanted, real-time machine learning architecture which automatically sets-up and ingests data both in real-time and batch, transforms data and stores it into our proprietary feature/vector store. Ranking models are continuously optimized and fine-tuned based on real-time feedback ensuring customers are seeing the most relevant and up-to-date results possible.

From a machine-learning perspective we use state-of-the-art large scale neural encoding models to understand multi-modal data types such as image, text, audio and tabular data. We provide an exhaustive library of retrieval, ranking and ordering algorithms which are selected based on the specified model definition.

We use both AWS and GCP for cloud. Kubernetes for serverless infrastructure. Python, Javascript and Rust for languages.