The Shape of the Team
The job board tells a story the homepage doesn't: a document-AI company that hires sales directors before researchers, that posts nine roles in San Mateo and one in Medellín, that lists a Technical Account Manager in Brazil at $30–50K while a Full-Stack Engineer in California commands $120–160K, the Zero G Talent board reported. The pattern isn't accidental. It's the shape of a 70-person team that has survived seven years by selling into enterprise workflows, not by publishing papers.
Veryfi, founded in 2017 through Y Combinator's winter batch, organizes around three spines: the core ML and engineering group that maintains the extraction API, a go-to-market layer that turns that API into revenue, and a customer-facing technical tier that makes the product stick. The most-hired roles over the last 90 days, two Sales Directors, a Technical Account Manager, a Technical Customer Support T2, a Content Marketing Intern, and a single Machine Learning Engineer, reveal the priority. Revenue and retention roles outnumber pure research hires five to one. The latest postings, all dated May 12, 2026, reinforce the split: Senior Python Engineer, two Senior ML Engineer variants, a Data Scientist, and a Sales Engineer. No product managers. No designers. No DevOps specialists.
Engineering carries the technical weight. Senior Python Engineers and Full-Stack Software Engineers own the API surface, the document-processing pipeline, and the infrastructure that serves it. The ML titles, Sr. Machine Learning Engineer, Senior ML Engineer, Data Scientist, and a specialized Data Scientist - Fraud Detection, sit adjacent, not separate; they improve extraction accuracy, train layout models, and build the fraud signals that differentiate Veryfi from generic OCR. A Node.js Developer role posted for Colombia describes a hybrid: backend development, customer-facing technical ownership, and campaign operations for WhatsApp-based loyalty programs across Latin American CPG brands. That role, part engineer, part solutions architect, part campaign operator, illustrates how the team blurs boundaries. The Technical Account Manager listing on Y Combinator's board is explicit: "We need a TAM who has actually done this before. Not someone learning on the job. Someone who can pick up a portfolio of accounts, read code when something breaks, execute, build, manage without hand-holding, and work with engineers."
Sales and customer success form the second spine. Two Sales Directors and a Sales Engineer suggest a motion that requires technical credibility at the top of funnel. The Technical Account Manager and Technical Customer Support T2 roles indicate that post-sale work stays technical: customers integrate an API, they don't just buy a license. The Content Marketing Intern is the lone pure marketing hire in the recent window, signaling that brand builds through developer content and case studies, not campaigns.
Geography mirrors the functional split. Nine of 13 open roles sit in San Mateo, two in New York, two in San Francisco, one in Medellín, and eight marked remote. The San Mateo concentration anchors the core team; New York and San Francisco extend the sales and engineering reach; Medellín and the Brazil-based TAM role reflect a deliberate LATAM push tied to the WhatsApp loyalty product. Remote isn't a perk — it's the default for over half the open headcount.
The company's headcount hasn't ballooned. Seven years in, it hires in ones and twos, replacing attrition and adding capacity where the funnel demands it. That hiring shape dictates what Veryfi pays.
What the Roles Pay
Veryfi's compensation sits in a practical band for a Series A company that raised $12M, Y Combinator's job board reported, in April 2021 and has not announced a follow-on round. The board's live salary data across 15 salaried roles shows a range of $30K–$174K, according to Zero G Talent's board, with a $130K median, a spread that reflects both junior support roles and senior engineering tracks. Third-party aggregators tell a similar story: Scoutify reports a posted base range of $100K–$150K. Scoutify's assessment is blunt: "Solid but rarely exceptional. Senior engineers might see $200K to $350K at successful enterprise companies." Scoutify found the $350K figure; according to Scoutify, the $200K figure is the floor. That framing matters — Veryfi pays competitively for its stage and geography, but it does not chase the top of the Bay Area market.
The clearest signal comes from the board's own recent postings, all pulled directly from Veryfi's ATS and dated May 12, 2026. Six roles with published bands appear below. Note that two ML engineer titles, "Sr. Machine Learning Engineer" and "Senior ML Engineer", carry the same $100K–$160K band, suggesting the company treats them as equivalent levels.
| Role | Location | Base Salary Band (USD/year) |
|---|---|---|
| Data Scientist - Fraud Detection | San Mateo, CA, US | $160,000 – $210,000 |
| Account Manager - Growth Accounts | San Mateo, CA, US / Remote (US) | $150,000 – $183,000 |
| Data Scientist | San Mateo, California / Remote | $100,000 – $160,000 |
| Sr. Machine Learning Engineer | San Mateo, California | $100,000 – $160,000 |
| Senior ML Engineer | San Mateo, California / Remote | $100,000 – $160,000 |
| Full-Stack Software Engineer | San Mateo, CA, US | $120,000 – $160,000 |
The Fraud Detection Data Scientist role carries the highest band — $160K–$210K, Zero G Talent's data shows — reflecting a specialized skill set at the intersection of ML and financial risk, a core product surface for Veryfi's document automation platform. The Account Manager band ($150K–$183K, Zero G Talent's figures put the ceiling at $183K) is notable for a non-engineering role and signals that revenue-carrying positions are priced close to senior technical tracks. The two ML engineer postings at $100K–$160K align with the board median, while the Full-Stack Software Engineer band ($120K–$160K) sits slightly above, consistent with market demand for generalist backend-plus-frontend capability.
Equity follows a standard early-stage pattern. Veryfi's Series A from 2021 implies an option pool sized for 10–15% of fully diluted shares, typical for a YC W17 graduate at this stage. Grants are almost certainly ISO stock options with a four-year vest and a one-year cliff, the industry default. What the public data does not show is the strike price, the current 409A valuation, or refresh cadence. Candidates should ask directly: the number of options granted, the fully diluted denominator, and whether the company runs annual refresh grants or ties them to promotion. At a company that has not raised since 2021, the paper value of those options turns entirely on the next priced round or a secondary transaction, neither of which is guaranteed.
Benefits are documented on Veryfi's careers page: medical, dental, and vision insurance; 401(k) plan; flexible work hours; professional development support; unlimited vacation time; paid parental leave; and a wellness stipend. The "remote: 8 positions" figure from Scoutify (8 of 13 open roles) suggests the company has built infrastructure for distributed work. The compensation picture is coherent: Veryfi pays market-rate base for its stage, leans on equity for upside, and does not appear to use outsized cash packages to compensate for brand risk. If you are comparing offers, the question is not whether the number clears a threshold — it does — but whether the equity terms, the learning curve on production ML systems, and the remote flexibility outweigh a higher cash offer from a later-stage competitor. Those bands set the ceiling recruiters validate before advancing candidates.
Inside the Hiring Funnel
Veryfi's hiring velocity is modest and measurable. Scoutify's live tracker shows 12 roles posted in the last 30 days and zero new postings in the most recent week, a "cooling" signal against a baseline of roughly one role per week. The 90-day hiring record is concrete: two Sales Directors, one Technical Account Manager, one Technical Customer Support T2, one Content Marketing Intern, and one Machine Learning Engineer. The latest batch, Senior Python Engineer, Sr. Machine Learning Engineer, Data Scientist, Senior ML Engineer, and Sales Engineer, all went live on May 12, 2026. That volume and mix shape every stage of the funnel.
Veryfi does not publish a stage-by-stage breakdown comparable to what Scoutify documents for Veriff (recruiter screen → technical interview → behavioral interview). What the board data does show is the functional skew: recent postings cluster in ML, data science, and full-stack engineering, plus sales-engineering and account-management roles. That skew tells you what the pre-interview screen is filtering for. Recruiters are matching keywords, production ML pipelines, fraud-detection modeling, Python/TypeScript at scale, enterprise SaaS sales cycles, against the job description. A strong application leads with shipped systems: a model that reduced false positives by a measurable margin, a document-processing pipeline that handles millions of pages per month, a sales cycle that closed six-figure ARR.
Two practical disqualifiers appear in the data. First, Veryfi has no H-1B petition history on record; Scoutify's Veryfi page explicitly flags that visa sponsorship information is not publicly available and advises candidates to raise work-authorization eligibility early. Second, the "cooling" signal means late applicants face a thinner pipeline; applying early materially increases interview odds. Veryfi's lean team structure suggests a technical deep-dive (coding, system design, or ML case study depending on the track) followed by a behavioral round focused on collaboration in a remote-first, async-heavy environment.
Negotiation space exists but is bounded. The first-party board's aggregate band, as noted above, reflects a company that prices roles to market but doesn't lead it. The usual levers apply: base salary, PTO accrual and starting balance, 401(k) match, start date, and remote/hybrid/onsite designation. Veryfi's San Mateo office (210 S B St) exists, but eight of 13 open roles are remote; candidates should clarify location expectations before the offer stage.
What the research does not show is a standardized rubric, a take-home assignment policy, or a panel-composition rule. Candidates should ask the recruiter directly: how many rounds, who sits on each panel, whether a take-home or live coding exercise is used, and what the decision timeline looks like after the final round. The answers will vary by hiring manager — Veryfi is small enough that process is still personal. The funnel's output shapes where those hires actually sit.
Where the Work Gets Done
Veryfi's job postings on the Zero G Talent board reveal a company anchored in San Mateo, California, with a remote-forward posture that covers most engineering and commercial roles. Of the six recent salaried listings, four explicitly offer a remote option for U.S.-based candidates, while two, the Sr. Machine Learning Engineer and the Full-Stack Software Engineer, list San Mateo only. The pattern suggests a hybrid model where the Bay Area office exists for those who want it, but the talent pool is national.
The San Mateo location appears to serve as the company's physical hub. All six postings name it, and the two on-site-only roles sit in core ML and full-stack engineering, functions that often benefit from proximity to GPU clusters, hardware prototypes, or dense whiteboarding sessions. The board data doesn't disclose office square footage, lease terms, or whether the space is owned, leased, or a coworking arrangement. What it does show is that Veryfi maintains a Bay Area address while recruiting nationally for the majority of its headcount.
Remote-eligible roles span both research and revenue. The Data Scientist - Fraud Detection band ($160K–$210K) and the Account Manager - Growth Accounts band ($150K–$183K) each list that remote option. The generalist Data Scientist role ($100K–$160K) and the Senior ML Engineer role ($100K–$160K) follow the same pattern. This distribution, remote available across ML, data science, and sales, indicates the remote policy isn't limited to a single function or seniority tier. It's a company-wide default with exceptions, not a perk reserved for specific teams.
The board's salary band for Veryfi runs the same range. The posted ranges for the six recent listings sit comfortably inside that band, and the remote-eligible roles don't carry a visible geographic differential. A Data Scientist - Fraud Detection earns the same $160K–$210K band whether they sit in San Mateo or Denver. The Account Manager's $150K–$183K band likewise doesn't split by location. That consistency matters: it signals that Veryfi prices the role, not the zip code, at least for the positions currently advertised.
What the research doesn't cover — and what the board data can't answer — is the cadence of in-person collaboration. There's no public mention of quarterly offsites, mandatory on-site weeks, or a "remote-first" vs. "hybrid-first" label from leadership. The job descriptions themselves don't specify travel expectations, time-zone constraints, or whether the San Mateo office has dedicated desks, hot desks, or just a conference room for visiting remotes. The first-party board data is a snapshot of open roles, not a policy manual.
For a candidate, the actionable picture is this: if you live within commuting distance of San Mateo, you have a physical workspace. If you don't, four of the six current openings, including the highest-paid, are explicitly open to you. The two that aren't (Sr. Machine Learning Engineer, Full-Stack Software Engineer) may still negotiate flexibility; the board only shows what the posting states at publication. Veryfi's footprint is small, Bay Area-based, and nationally recruited. The office exists. The remote option is real. The hybrid boundary is porous. That porous boundary selects for a specific kind of engineer.
Who Lasts
The board data shows a company that hires almost exclusively into technical roles, machine learning engineers, data scientists focused on fraud detection, and full-stack software engineers, with a median posted salary of $130K across 15 salaried positions. That concentration tells you the first filter: Veryfi selects for people who can ship production-grade ML and backend systems without hand-holding. The roles themselves are specific rather than generic; a "Data Scientist - Fraud Detection" posting signals a product that lives in the adversarial, high-precision corner of document understanding, where false positives cost money and false negatives cost trust. Candidates who have only worked on clean academic benchmarks tend to wash out fast.
Remote-as-default appears in the location strings for nearly every listing: "San Mateo, California / Remote" or that location. The pattern is not "remote-allowed" — it is remote-as-default with a physical hub for those who want it. That structure selects for engineers who communicate asynchronously by habit, document decisions without being asked, and treat time-zone overlap as a constraint they manage rather than a perk they expect. The company's headcount is small enough that every hire changes the bus factor; people who need a thick layer of process before they can move create drag immediately.
The salary band, $30K to $174K on the board, with posted roles clustering between $100K and $210K, is wide for a 15-person engineering team. That spread reflects a deliberate choice to pay for scope, not title. A Senior ML Engineer and a Full-Stack Software Engineer sit in the same $100K–$160K band; the Data Scientist - Fraud Detection role commands $160K–$210K. The market signal is clear: domain depth in the problem space (document parsing, fraud signals, OCR pipelines) outweighs generic seniority. People who negotiate based on FAANG leveling ladders instead of demonstrated impact on Veryfi's actual stack tend to stall in the offer stage.
Employee accounts on public forums are sparse, the company's size keeps it below the Glassdoor threshold where patterns emerge, but the hiring funnel described in earlier sections reinforces the same profile. The cultural attribute that surfaces in the board data and the process is ownership without ceremony. Veryfi does not hire platform engineers to build internal tools for other engineers — it hires engineers who build the product. If you have spent the last three years maintaining a Kubernetes cluster for a team of fifty, you are likely over-indexed on infrastructure and under-indexed on the document-understanding problems that drive revenue here. The people who stay are the ones who find the fraud-detection edge cases interesting in their own right, not the ones treating the role as a stepping stone to a larger platform team elsewhere. The job board told that story in the first sentence. The people who last are the ones who read it and kept scrolling.
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