About Daloopa, Inc. Daloopa accelerates decision-making for investment professionals by transforming complex financial data into actionable intelligence through AI-powered infrastructure. Founded by Thomas Li, Daloopa au…
About Daloopa: Daloopa accelerates decision-making for investment professionals by transforming complex financial data into actionable intelligence through AI-powered infrastructure. Founded by Thomas Li, Daloopa automat…
Skills: Engineering Management, Team Leadership, Distributed Systems, Data Processing, Machine Learning
About Daloopa, Inc. Daloopa accelerates decision-making for investment professionals by transforming complex financial data into actionable intelligence through AI-powered infrastructure. Founded by Thomas Li, Daloopa au…
Skills: Python, Django, Scrapy, Relational data modeling, Backend development
About the role Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $202,500 - $222,000 annualized salary + equity + benefits (This range is reflective of level of c…
Skills: Financial modeling, Microsoft Excel, LLM workflows, APIs, Technical discovery
About the role Location: Toronto, Canada (this role is fully remote; travel to our HQ in NYC will be expected) Compensation: CAD $240,000 - $270,000 annualized salary + equity + benefits (This range is reflective of leve…
About the Role Location: London (hybrid schedule) Compensation: £59,500-£64,000 OTE + equity + benefits (This range is reflective of level of contribution. Candidates who fully match what we’re looking for in this role w…
Skills: Outbound prospecting, Sales development, Business development, Lead qualification, Communication
Key Responsibilties • Build and maintain detailed historical financial models for both public and private companies. • Update financial data with the latest earnings releases and other relevant financial disclosures. • A…
Skills: Financial modeling, Data analysis, Microsoft Excel, Financial statements, Analytical techniques
Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $95,000 - $125,000 annualized + equity + benefits (This range is reflective of level of contribution. Candidates…
Skills: General Ledger Accounting, Month-end Close, US GAAP, Financial Reporting, Account Reconciliation
About the Role Location: New York City (Hybrid office/remote schedule) Compensation: $60-75k base + commission + equity + benefits (This range is reflective of level of contribution. Candidates who fully match what we’re…
About the role Location: Toronto, Canada (Remote) Compensation: $173k - $190k CAD annualized + equity + benefits (This range is reflective of level of contribution. Candidates who fully match what we’re looking for in th…
Skills: Product Design, Information Architecture, B2B SaaS Design, Figma, Prototyping
About The Role Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $150,500 – $167,000 OTE (base + variable) + equity + benefits (This range is reflective of level …
Role Overview: We are looking to hire a Senior Finance Analyst / Lead Analyst to strengthen our Finance team at Daloopa. This role will focus on driving financial planning, reporting, and core accounting operations, whil…
Gautam Buddha Nagar, Uttar Pradesh, India · On-site
Entry level$101M raised
Role Overview: We are currently expanding our Solutioning function at Daloopa and are looking for an enthusiastic and detail-oriented Data Analyst to join the team. The ideal candidate should have strong analytical skill…
Skills: Ms Excel, Sql, Power Bi, Data Analysis, Data Visualization
About the role Location: New York City (Hybrid office/remote schedule) Compensation: $205k - $225k annualized + equity + benefits (This range is reflective of level of contribution. Candidates who fully match what we’re …
Skills: Product Management, AI Product Development, LLM Implementation, Roadmap Strategy, User Discovery
About Daloopa, Inc. The data layer behind how AI actually works in finance. Daloopa turns messy financial disclosures into audit-grade, model-ready data used by institutions like Morgan Stanley. Its infrastructure sits b…
About Daloopa, Inc. The data layer behind how AI actually works in finance. Daloopa turns messy financial disclosures into audit-grade, model-ready data used by institutions like Morgan Stanley. Its infrastructure sits b…
About Daloopa, Inc. The data layer behind how AI actually works in finance. Daloopa turns messy financial disclosures into audit-grade, model-ready data used by institutions like Morgan Stanley. Its infrastructure sits b…
Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $166,000 – $205,000 OTE (base + variable) + equity + benefits (This range is reflective of level of contribution…
Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $166,000 – $205,000 OTE (base + variable) + equity + benefits (This range is reflective of level of contribution…
Skills: Sales Enablement, Program Management, Go-To-Market Strategy, Onboarding, Competitive Intelligence
Location: New York City (Hybrid). In-office at least three days per week (Tues, Wed, & Thurs) Compensation: $185,000 – $205,000 OTE (base + variable) + equity + benefits (This range is reflective of level of contribution…
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Full-time
Posted 5d ago
~40 hrs/week
Responsibilities
You will build and scale the supervised learning platform that integrates human-in-the-loop corrections with ML models. Additionally, you will design extraction pipelines to transform financial documents into structured, audit-ready data.
Requirements
The role requires 4+ years of professional backend engineering experience with strong expertise in Python and Django. Candidates must have hands-on experience integrating ML models or LLMs into production and working with distributed systems.
Full job description
About Daloopa, Inc.
Daloopa accelerates decision-making for investment professionals by transforming complex financial data into actionable intelligence through AI-powered infrastructure. Founded by Thomas Li, Daloopa automates the extraction, organization, and delivery of deeply sourced, audit-ready financial datasets, enabling clients to update models faster, reduce errors, and focus on higher-value analysis. With innovations like MCP for Financial Services, which connects verified data directly to AI agents and industry workflows, Daloopa is trusted by leading global institutions such as Morgan Stanley and supported by prominent investors.
The Role:
Daloopa's mission is to become the market leader in high-quality, actionable data for the world's top investment professionals. We're judged on three things: coverage, speed, and accuracy. Whether a hedge fund analyst can find the right number, get it fast, and trust it absolutely. The companies in our space (AlphaSense, , Refinitiv, Fiscal.ai and surface." Daloopa is solving ground truth at scale. FinancialReports.eu) mostly solve "find What makes us different is the loop. Our analysts review, correct, and enrich every extraction from financial documents. Those corrections become training signal for the next generation of our models. Models get sharper. Analysts get faster. Coverage expands, speed compounds, and accuracy keeps climbing in a way LLM-only competitors can't match. That's why Morgan Stanley trusts our numbers, and why this company has a moat.
As a Senior Backend Engineer on the ML side, you'll build the platform that makes the loop work. The systems that turn analyst corrections into structured training signal. The pipelines that move PDFs and HTML filings into model-ready data, route extraction work to humans when models are uncertain, and feed the result back into the next training cycle. The domain spans every public market, every accounting convention, every reporting nuance across geographies, and the platform you build has to scale across all of it. If you're excited by AI systems where humans and models actually collaborate (rather than chatbots pretending to know things), this is the role.
What You'll Lead and Transform:
• Build and scale the supervised learning platform that turns analyst corrections into training data.
• The connective tissue between our human-in-the-loop process and our models.
• Design and operate the extraction pipelines that turn PDFs and HTML filings into structured, audit-ready data, in partnership with the ML team.
• Build the routing and uncertainty-aware systems that decide when a model can act alone and when an analyst needs to weigh in.
• Integrate LLMs and ML models into production via API endpoints and inference pipelines, with the reliability and observability our clients require.
• Define database schemas and architectural decisions for performance, scalability, and resilience across a domain that spans every public market and accounting convention.
• Champion clean, maintainable code through reviews, tests, and clear documentation.
What Sets You Up for Success
• 4+ years of professional backend engineering experience.
• Strong expertise in Python and Django (or equivalent backend frameworks).
• Hands-on experience integrating ML models or LLMs into production: model serving, inference APIs, vector stores.
• Deep understanding of relational and non-relational databases (PostgreSQL, MySQL, Redis, DynamoDB).
• Experience with distributed systems, caching, and asynchronous task queues (Celery or equivalent).
• Track record of leading backend or ML-integrated projects end-to-end.
• Genuine interest in the problem domain. Financial data, supervised learning systems, or human-in-the-loop AI.
• You should be the kind of person who reads the AlphaSense product launches and has opinions.
Bonus Points for
• Experience building human-in-the-loop or active learning systems where labeled data quality directly determines model performance.
• Experience extracting structured data from messy real-world documents (PDFs, HTML, scanned content) at scale.
• Background in fintech, financial data, or other domains where data quality is mission-critical and audit trails matter.
• Familiarity with the financial fundamentals landscape: 10-Ks, 10-Qs, transcripts, segment reporting, non-GAAP reconciliations.
• Prior experience at growth-stage startups where you've scaled systems through major growth phases.
Delivering trusted financial data across 6,000+ global tickers that powers AI agents, LLMs, and leading financial institutions worldwide.
Analysts at the top investment firms use our workflow solutions to save valuable time and accelerate their decision making. We also provide the core AI data infrastructure that underpins the best financial agents and are the partner of choice for the leading global AI companies, including OpenAI, Anthropic and Perplexity.
Get in touch at [email protected].
Offices: 122 E 42nd St, New York, NY 10168, US · Noida Greater Noida Expressway, Noida, Uttar Pradesh, IN
SoftwareAnalyticsFinancial ServicesArtificial Intelligence (AI)Big Data
Delivering trusted financial data across 6,000+ global tickers that powers AI agents, LLMs, and leading financial institutions worldwide.
Analysts at the top investment firms use our workflow solutions to save valuable time and accelerate their decision making. We also provide the core AI data infrastructure that underpins the best financial agents and are the partner of choice for the leading global AI companies, including OpenAI, Anthropic and Perplexity.
Get in touch at [email protected].
Offices: 122 E 42nd St, New York, NY 10168, US · Noida Greater Noida Expressway, Noida, Uttar Pradesh, IN
SoftwareAnalyticsFinancial ServicesArtificial Intelligence (AI)Big Data