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

Shaped’s Account Executive will be closing new business through a technical, consultative sales process to high growth, venture-backed companies. Our Account Executive will identify new business opportunities, new prospective customers, and new verticals for us to sell into. You understand technical products and services and enjoy communicating their value to customers. 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

• Identify prospective customers, generate and convert opportunities for net new business
• Design and execute dynamic sales strategies to meet and exceed revenue quotas
• Analyze market landscapes and trends to define Shaped’s sales playbook.
• Take a consultative approach to sales by assessing customer goals and technical challenges
• Become an expert on Shaped and answer questions about the product
• Lead presentations and demos of Shaped product and collaborate with ML Engineers
• Negotiate prices and terms
• Work closely with Engineering, Machine Learning Engineering and Marketing teams

Who you are

• 5+ years of experience closing technical sales (2+ in a start-up environment - ideally with experience in enterprise B2B / developer tools)
• Proven history of exceeding quota targets at high-growth organizations by navigating and developing new sales processes
• History of strategic and creative pipeline generation tactics
• Excellent written and verbal communication, an entrepreneurial mindset with critical problem-solving and analytical skills
• Excellent at building relationships with prospects and customers
• Confidence in creating and presenting complex presentations to technical buyers across multiple segments and industries
• Ability to shepherd complex POCs through key milestones in conjunction with ML Engineers, our engineering org, and other Shaped stakeholders
• Scrappiness in helping design and operate GTM tech stack (Hubspot, Outreach, 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.