Member of Technical Staff, Model Training
At a glance
Senior Software Engineering role at Parallel Web Systems. San Francisco · full-time · $150,000–$300,000 base.
techroles summary, based on the employer's posting.
What you'll do
- Build the training pipeline for models used in search ranking, classification, and query handling, as well as agent planning and execution
- Turn real product activity into useful training examples, then fine-tune and assess the models
- Release models safely to systems serving millions of users
What you bring
- You have deep knowledge of current model training, including transformer fine-tuning, data selection, and label quality
- You can connect ranking, retrieval, and agent behavior when deciding how models should be trained
- You hold a bachelor’s degree or have an equivalent mix of education, training, and work experience
- You bring relevant preparation through coursework, training, or professional experience
Who this fits
This senior technical role suits you if you want to apply model research to products and systems used at scale. The team works in person at its Palo Alto headquarters or San Francisco office.
From the employer
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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