Posting record
Open 12+ days
- Parallel's site dates the posting
- Ghostless first sees this listing
- Last checked: still up
How we know
It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.
Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Parallel, so its true age is longer.
Last checked Nov 4, 2026.
How well do you match?
See how much of this posting your resume shows, and what it's missing.
Upload your resumeWhat it asks of you
- Bachelor's degree asked for
What the posting discloses
- Pay
- $150k to $300k a year USD
Not stated: Real vacancy, AI screening.
Why these three
Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.
Skills mentioned
About the role
About us
Parallel is a web infrastructure company. Our products are used by leading businesses in sales, marketing, insurance, and coding to build best-in-class AI agents with flexible and powerful programmatic access to the web.
We've raised $230 million from Kleiner Perkins, Sequoia, Index Ventures, Spark Capital, Khosla Ventures, First Round, and Terrain to build the web for AIs. We're currently valued at $2 billion and we're forming a world-class team of engineers, designers, marketers, sellers, researchers, and operational experts to achieve our mission.
The role
You will own the training pipeline behind the models that power both Parallel’s search stack and Parallel’s agents. On the search side, that means the rankers, classifiers, and query models that surface the right information. On the agent side, that means the models that help our agents plan, reason, and execute high-value tasks over web data. You will build the path from real product usage to high-quality training data, fine-tune and evaluate these models rigorously, and ship them safely to traffic used by millions.
About you
Have deep intuition on modern models and training, including transformer fine-tuning, data curation, and the craft of label quality. Think rigorously about how ranking, retrieval, and agent behavior inform one another, and how to train models that serve all three. You care about your research being applied to product and systems that millions use.
You might be a good fit if you have
- Bachelor's degree or equivalent combination of education, training, and professional experience
- A field relevant to the role as demonstrated through coursework, training, or professional experience
- Years of experience required will correlated with the internal job level requirements for this position
Life at Parallel
Our team works fully in-person , between our Palo Alto HQ and San Francisco office. We’re a flat, talent-dense organization dedicated to solving technical and creative problems.
We seek like-minded individuals who share our passion for applying science, creativity, and consistency to big and complex problems with equally big outcomes. These are our values
- Own customer impact: It’s on us to ensure real-world outcomes for our customers.
- Obsess over craft: Perfect every detail because quality compounds.
- Accelerate change : Ship fast, adapt faster, and move frontier ideas into production.
- Create win-wins : Creatively turn trade-offs into upside.
- Make high-conviction bets : Try and fail. But succeed an unfair amount.
Compensation & benefits
- Competitive salary
- Generous equity
- Visa sponsorships
- 401K plans
- Daily lunch & office snacks
- Dinner at the office
- Unlimited vacation
- Caltrain pass reimbursement
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