採用
福利厚生
•Unlimited Pto
•Healthcare
•401(k)
•Equity
•Meals
•Parental Leave
必須スキル
Full-Cycle Recruiting
Technical Recruiting
Sourcing
Stakeholder Management
Candidate Assessment
About Hebbia
The AI platform for investors and bankers that generates alpha and drives upside.
Founded in 2020 by George Sivulka and backed by Peter Thiel and Andreessen Horowitz, Hebbia powers investment decisions for Black Rock, KKR, Carlyle, Centerview, and 40% of the world’s largest asset managers. Our flagship product, Matrix, delivers industry-leading accuracy, speed, and transparency in AI-driven analysis. It is trusted to help manage over $30 trillion in assets globally.
We deliver the intelligence that gives finance professionals a definitive edge. Our AI uncovers signals no human could see, surfaces hidden opportunities, and accelerates decisions with unmatched speed and conviction. We do not just streamline workflows. We transform how capital is deployed, how risk is managed, and how value is created across markets.
Hebbia is not a tool. Hebbia is the competitive advantage that drives performance, alpha, and market leadership.
The Team
At Hebbia, the Talent team is not a support function. It’s a core driver of the company’s ability to build, ship, and scale category-defining AI. We partner directly with founders, executives, and functional leaders to design teams that can solve the hardest knowledge-work problems in the world.
The Talent team runs high-signal, high-conviction recruiting processes, combining deep role fluency, rigorous assessment, and decisive execution to consistently raise the bar. More than filling seats, we act as strategic advisors and operators.
The Role
As a Recruiter at Hebbia, you’ll play a pivotal role in scaling the team behind our Matrix platform by identifying, engaging, and closing exceptional talent across Engineering, Product, and Design (EPD) teams. You’ll be a strategic partner to hiring managers and leadership by shaping hiring plans, translating business priorities into crisp role definitions, and guiding candidates through a high-bar, high-touch process. Beyond filling roles, you’ll help build the foundation of Hebbia’s culture and velocity by ensuring we attract people who can reimagine how work gets done and can move fast in ambiguity.
Responsibilities
-
Own EPD talent pipeline: Lead full-cycle recruiting for Hebbia’s commercial organization, including Engineering, Product, Design and Security.
-
Hunt for elite EPD talent: Go far beyond inbound. Proactively source and engage top-tier technical experts through targeted outreach, creative search strategies, and deep network leverage.
-
Be the face of Hebbia in the market: Serve as the first touchpoint for technical candidates. Clearly articulate Hebbia’s ambition, product differentiation, and growth trajectory ensuring every candidate is left with a compelling understanding of the opportunity.
-
Deliver a world-class candidate experience: Ensure every candidate interaction is thoughtful, transparent, and high-integrity.
Who You Are
-
2+ years of EPD recruiting experience, ideally at a fast-growing startup
-
Proven track record rapidly scaling technical teams
-
Creativity in problem-solving and innovating across all stages of the hiring cycle
-
Experience aligning internal stakeholders on job descriptions, compensation bands and interview processes
-
Autonomous and excited about taking ownership over major hiring initiatives
-
Extreme passion for learning and growth
総閲覧数
0
応募クリック数
0
模擬応募者数
0
スクラップ
0
類似の求人
Hebbiaについて

Hebbia
Series BHebbia is an American technology company that develops artificial intelligence and automation tools for financial and legal research. The company was founded in 2020 by George Sivulka, a former Stanford University PhD student, with its headquarters in New York City.
51-200
従業員数
New York
本社所在地
$1.3B
企業価値
レビュー
4.0
10件のレビュー
ワークライフバランス
3.2
報酬
3.8
企業文化
4.1
キャリア
4.2
経営陣
3.5
75%
友人に勧める
良い点
Flexible work hours and remote options
Great team culture and supportive environment
Good benefits and perks
改善点
Heavy workload and overwhelming demands
Long hours during peak projects
Compensation could be better
給与レンジ
12件のデータ
Junior/L3
Junior/L3 · Analyst
1件のレポート
$156,000
年収総額
基本給
$120,000
ストック
-
ボーナス
-
$156,000
$156,000
面接体験
62件の面接
難易度
3.4
/ 5
期間
14-28週間
内定率
37%
体験
ポジティブ 66%
普通 20%
ネガティブ 14%
面接プロセス
1
Phone Screen
2
Technical Interview
3
System Design
4
Behavioral
5
Team Fit
よくある質問
Tell me about a challenging project
System design question
Coding problem
Why this company
ニュース&話題
Show HN: An unstructured data workspace for data transformations with LLM
hi HN!<p>a couple of months ago I had to analyze a few thousand audio recordings to help identify issues with customer support. i was able to get some raw high-level initial results with python scripts invoking LLM APIs, but they were too general and unhelpful. writing basic prompts is easy, but tuning them and making them specific enough to ensure no faint signal is missed is hard. you need to iterate through the data with an initial prompt, segment the data into different buckets, chain anothe
HN
·
3w ago
·
4
Official Reddit Home of Hebbia | A New Era of Institutional Intelligence
Founded in 2020 by George Sivulka, Hebbia was purpose-built to meet the demands of finance. Today, Hebbia is the leading AI platform for institutional finance—backed by Andreessen Horowitz, Peter Thiel, and Index Ventures. We are trusted by investment banks and over 40% of the largest asset managers by AUM trust Hebbia to work the way they do: fast, accurate, and collaborative across the full deal cycle. We have joined Reddit to connect with the financial professionals who use Hebbia to move f
·
3w ago
·
1
·
1
Seyfarth Leads Next Phase of Deal Execution and Diligence Through AI Partnership with Hebbia - Business Wire
Business Wire
News
·
5w ago
Neuromorphic sphere topology Hebbian learning as a path to grounded intelligence
I've been working on a hypothesis and want to get feedback from people who know more than I do. The hypothesis Intelligence might be a phase transition at scale, not an algorithmic problem. Fly: 100k neurons — no generalization Mouse: 70M — basic associative learning Human: 86B — abstract reasoning This doesn't look like a smooth curve. It looks like thresholds. If that's true, then no amount of architectural cleverness crosses it — only scale + grounding does. The grounding probl
HN
·
5w ago
·
1




